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Books and Theses
- 2014
[b1]Wojciech Samek:
On robust spatial filtering of EEG in nonstationary environments. Berlin Institute of Technology, 2014
Journal Articles
- 2025
- [j65]Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon:
Explaining predictive uncertainty by exposing second-order effects. Pattern Recognit. 160: 111171 (2025) - 2024
- [j64]Luca Longo
, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf:
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions. Inf. Fusion 106: 102301 (2024) - [j63]Sören Becker, Johanna Vielhaben, Marcel Ackermann, Klaus-Robert Müller, Sebastian Lapuschkin, Wojciech Samek:
AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark. J. Frankl. Inst. 361(1): 418-428 (2024) - [j62]Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek:
Explainable AI for time series via Virtual Inspection Layers. Pattern Recognit. 150: 110309 (2024) - [j61]Daniel Becking, Karsten Müller, Paul Haase, Heiner Kirchhoffer, Gerhard Tech, Wojciech Samek, Heiko Schwarz, Detlev Marpe, Thomas Wiegand:
Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication. IEEE Trans. Multim. 26: 6848-6863 (2024) - [j60]Jacob R. Kauffmann, Malte Esders, Lukas Ruff, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
From Clustering to Cluster Explanations via Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(2): 1926-1940 (2024) - [j59]Leon Witt, Usama Zafar, KuoYeh Shen, Felix Sattler, Dan Li, Songtao Wang, Wojciech Samek:
Decentralized and Incentivized Federated Learning: A Blockchain-Enabled Framework Utilising Compressed Soft-Labels and Peer Consistency. IEEE Trans. Serv. Comput. 17(4): 1449-1464 (2024) - 2023
- [j58]Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond explaining: Opportunities and challenges of XAI-based model improvement. Inf. Fusion 92: 154-176 (2023) - [j57]Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li:
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. IEEE Internet Things J. 10(4): 3642-3663 (2023) - [j56]Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller:
Evaluating deep transfer learning for whole-brain cognitive decoding. J. Frankl. Inst. 360(13): 9754-9787 (2023) - [j55]Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond. J. Mach. Learn. Res. 24: 34:1-34:11 (2023) - [j54]Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
From attribution maps to human-understandable explanations through Concept Relevance Propagation. Nat. Mac. Intell. 5(9): 1006-1019 (2023) - [j53]Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni, Simon Colreavy-Donnelly, Wojciech Samek, Miguel A. Molina-Cabello, Ezequiel López-Rubio:
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. IEEE Trans. Artif. Intell. 4(2): 282-291 (2023) - [j52]Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. Trans. Mach. Learn. Res. 2023 (2023) - [j51]Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jérôme Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti:
Data Models for Dataset Drift Controls in Machine Learning With Optical Images. Trans. Mach. Learn. Res. 2023 (2023) - [j50]Felix Sattler, Tim Korjakow, Roman Rischke, Wojciech Samek:
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5531-5543 (2023) - [j49]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Langevin Cooling for Unsupervised Domain Translation. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7675-7688 (2023) - 2022
- [j48]Djordje Slijepcevic, Fabian Horst, Sebastian Lapuschkin, Brian Horsak, Anna-Maria Raberger, Andreas Kranzl, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer:
Explaining Machine Learning Models for Clinical Gait Analysis. ACM Trans. Comput. Heal. 3(2): 14:1-14:27 (2022) - [j47]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Explain and improve: LRP-inference fine-tuning for image captioning models. Inf. Fusion 77: 233-246 (2022) - [j46]Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. Inf. Fusion 77: 261-295 (2022) - [j45]Andreas Holzinger, Matthias Dehmer, Frank Emmert-Streib, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurisica, Natalia Díaz Rodríguez:
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence. Inf. Fusion 79: 263-278 (2022) - [j44]Leila Arras, Ahmed Osman, Wojciech Samek:
CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations. Inf. Fusion 81: 14-40 (2022) - [j43]Simon M. Hofmann, Frauke Beyer, Sebastian Lapuschkin, Ole Goltermann, Markus Loeffler, Klaus-Robert Müller, Arno Villringer, Wojciech Samek, Anja Veronica Witte:
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage 261: 119504 (2022) - [j42]Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. IEEE Signal Process. Mag. 39(4): 40-58 (2022) - [j41]Heiner Kirchhoffer, Paul Haase, Wojciech Samek, Karsten Müller, Hamed Rezazadegan Tavakoli, Francesco Cricri, Emre B. Aksu, Miska M. Hannuksela, Wei Jiang, Wei Wang, Shan Liu, Swayambhoo Jain, Shahab Hamidi-Rad, Fabien Racapé, Werner Bailer:
Overview of the Neural Network Compression and Representation (NNR) Standard. IEEE Trans. Circuits Syst. Video Technol. 32(5): 3203-3216 (2022) - [j40]Felix Sattler, Arturo Marbán, Roman Rischke, Wojciech Samek:
CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding. IEEE Trans. Netw. Sci. Eng. 9(4): 2025-2038 (2022) - 2021
- [j39]Luis Oala, Cosmas Heiß, Jan MacDonald, Maximilian März, Gitta Kutyniok, Wojciech Samek:
Detecting failure modes in image reconstructions with interval neural network uncertainty. Int. J. Comput. Assist. Radiol. Surg. 16(12): 2089-2097 (2021) - [j38]Luis Oala, Andrew G. Murchison, Pradeep Balachandran, Shruti Choudhary, Jana Fehr, Alixandro Werneck Leite, Peter G. Goldschmidt, Christian Johner, Elora D. M. Schörverth, Rose Nakasi, Martin Meyer, Federico Cabitza, Pat D. Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Ahiale Akogo, Shada Alsalamah, Emre Kazim, Adriano S. Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saúl Calderón Ramírez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand:
Machine Learning for Health: Algorithm Auditing & Quality Control. J. Medical Syst. 45(12): 105 (2021) - [j37]Vignesh Srinivasan, Csaba Rohrer, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Robustifying models against adversarial attacks by Langevin dynamics. Neural Networks 137: 1-17 (2021) - [j36]Simon Wiedemann, Suhas Shivapakash, Daniel Becking, Pablo Wiedemann, Wojciech Samek, Friedel Gerfers, Thomas Wiegand:
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4Bit-Compact Multilayer Perceptrons. IEEE Open J. Circuits Syst. 2: 407-419 (2021) - [j35]Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller:
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109(3): 247-278 (2021) - [j34]Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller:
A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE 109(5): 756-795 (2021) - [j33]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. 115: 107899 (2021) - [j32]Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek:
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. IEEE J. Biomed. Health Informatics 25(5): 1519-1528 (2021) - [j31]Felix Sattler, Klaus-Robert Müller, Wojciech Samek:
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints. IEEE Trans. Neural Networks Learn. Syst. 32(8): 3710-3722 (2021) - 2020
- [j30]Nils Strodthoff, Patrick Wagner, Markus Wenzel, Wojciech Samek:
UDSMProt: universal deep sequence models for protein classification. Bioinform. 36(8): 2401-2409 (2020) - [j29]Johanna Vielhaben, Markus Wenzel, Wojciech Samek, Nils Strodthoff:
USMPep: universal sequence models for major histocompatibility complex binding affinity prediction. BMC Bioinform. 21(1): 279 (2020) - [j28]Clemens Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert:
Accurate and robust neural networks for face morphing attack detection. J. Inf. Secur. Appl. 53: 102526 (2020) - [j27]Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Tung Nguyen, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek:
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. IEEE J. Sel. Top. Signal Process. 14(4): 700-714 (2020) - [j26]Wojciech Samek:
Learning with explainable trees. Nat. Mach. Intell. 2(1): 16-17 (2020) - [j25]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand:
Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements. npj Digit. Medicine 3 (2020) - [j24]Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Compact and Computationally Efficient Representation of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 31(3): 772-785 (2020) - [j23]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3400-3413 (2020) - 2019
- [j22]Arturo Marbán, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals:
A recurrent convolutional neural network approach for sensorless force estimation in robotic surgery. Biomed. Signal Process. Control. 50: 134-150 (2019) - [j21]Ahmed Osman, Wojciech Samek:
DRAU: Dual Recurrent Attention Units for Visual Question Answering. Comput. Vis. Image Underst. 185: 24-30 (2019) - [j20]Guangtao Zhai, Ke Gu, Jiheng Wang, Wojciech Samek:
Quality perception of advanced multimedia systems. Digit. Signal Process. 91: 1-2 (2019) - [j19]Sebastian Bosse, Sören Becker, Klaus-Robert Müller, Wojciech Samek, Thomas Wiegand:
Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network. Digit. Signal Process. 91: 54-65 (2019) - [j18]Sergio Cruces, Rubén Martín-Clemente, Wojciech Samek:
Information Theory Applications in Signal Processing. Entropy 21(7): 653 (2019) - [j17]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate Neural Networks! J. Mach. Learn. Res. 20: 93:1-93:8 (2019) - [j16]Nils Strodthoff, Baris Göktepe, Thomas Schierl, Cornelius Hellge, Wojciech Samek:
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. IEEE J. Sel. Areas Commun. 37(11): 2573-2587 (2019) - 2018
- [j15]Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Methods for interpreting and understanding deep neural networks. Digit. Signal Process. 73: 1-15 (2018) - [j14]Stephan Kaltenstadler, Shinichi Nakajima, Klaus-Robert Müller, Wojciech Samek:
Wasserstein Stationary Subspace Analysis. IEEE J. Sel. Top. Signal Process. 12(6): 1213-1223 (2018) - [j13]Forooz Shahbazi Avarvand, Sarah Bartz, Christina Andreou, Wojciech Samek, Gregor Leicht, Christoph Mulert, Andreas K. Engel, Guido Nolte:
Localizing bicoherence from EEG and MEG. NeuroImage 174: 352-363 (2018) - [j12]Sebastian Bosse, Laura Acqualagna, Wojciech Samek, Anne K. Porbadnigk, Gabriel Curio, Benjamin Blankertz, Klaus-Robert Müller, Thomas Wiegand:
Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition. IEEE Trans. Circuits Syst. Video Technol. 28(8): 1694-1706 (2018) - [j11]Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment. IEEE Trans. Image Process. 27(1): 206-219 (2018) - 2017
- [j10]Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65: 211-222 (2017) - [j9]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller:
Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2660-2673 (2017) - 2016
- [j8]Wojciech Samek:
On robust spatial filtering of EEG in nonstationary environments. it Inf. Technol. 58(3): 150-154 (2016) - [j7]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. 17: 114:1-114:5 (2016) - [j6]Wojciech Samek, Duncan A. J. Blythe, Gabriel Curio, Klaus-Robert Müller, Benjamin Blankertz, Vadim V. Nikulin:
Multiscale temporal neural dynamics predict performance in a complex sensorimotor task. NeuroImage 141: 291-303 (2016) - 2015
- [j5]Siamac Fazli, Sven Dähne, Wojciech Samek, Felix Bießmann, Klaus-Robert Müller:
Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces. Proc. IEEE 103(6): 891-906 (2015) - [j4]Sven Dähne, Felix Bießmann, Wojciech Samek, Stefan Haufe, Dominique Goltz, Christopher Gundlach, Arno Villringer, Siamac Fazli, Klaus-Robert Müller:
Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data. Proc. IEEE 103(9): 1507-1530 (2015) - 2014
- [j3]Motoaki Kawanabe, Wojciech Samek, Klaus-Robert Müller, Carmen Vidaurre:
Robust Common Spatial Filters with a Maxmin Approach. Neural Comput. 26(2): 349-376 (2014) - 2013
- [j2]Alexander Binder, Wojciech Samek, Klaus-Robert Müller, Motoaki Kawanabe:
Enhanced representation and multi-task learning for image annotation. Comput. Vis. Image Underst. 117(5): 466-478 (2013) - [j1]Wojciech Samek, Frank C. Meinecke, Klaus-Robert Müller:
Transferring Subspaces Between Subjects in Brain-Computer Interfacing. IEEE Trans. Biomed. Eng. 60(8): 2289-2298 (2013)
Conference and Workshop Papers
- 2024
- [c89]Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin:
From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space. AAAI 2024: 21046-21054 - [c88]Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin:
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. CVPR Workshops 2024: 3491-3501 - [c87]Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin:
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. CVPR Workshops 2024: 3532-3541 - [c86]Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek:
AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers. ICML 2024 - [c85]Przemyslaw Biecek, Wojciech Samek:
Position: Explain to Question not to Justify. ICML 2024 - [c84]Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems, Roderick Murray-Smith, Shinichi Nakajima, Sebastian Lapuschkin, Stefano Ermon, Tolga Birdal, Manfred Opper, Christoph Knochenhauer, Luis Oala, Wojciech Samek:
Generative Fractional Diffusion Models. NeurIPS 2024 - [c83]Xiaoyan Yu, Jannik Franzen, Wojciech Samek, Marina M.-C. Höhne, Dagmar Kainmueller:
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models. xAI (2) 2024: 113-129 - [c82]Christian Tinauer, Anna Damulina, Maximilian Sackl, Martin Soellradl, Reduan Achtibat, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Reinhold Schmidt, Stefan Ropele, Wojciech Samek, Christian Langkammer:
Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification. xAI (2) 2024: 202-216 - 2023
- [c81]Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin, Wojciech Samek, Johanna Vielhaben:
XAI-based Comparison of Audio Event Classifiers with different Input Representations. CBMI 2023: 126-132 - [c80]Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Optimizing Explanations by Network Canonization and Hyperparameter Search. CVPR Workshops 2023: 3819-3828 - [c79]Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. CVPR Workshops 2023: 3829-3839 - [c78]Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR 2023: 16143-16152 - [c77]Karam Dawoud, Wojciech Samek, Peter Eisert, Sebastian Lapuschkin, Sebastian Bosse:
Human-Centered Evaluation of XAI Methods. ICDM (Workshops) 2023: 912-921 - [c76]Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. MICCAI (2) 2023: 596-606 - [c75]Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed M. Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala:
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. NeurIPS 2023 - 2022
- [c74]Klaus-Robert Müller, Armin W. Thomas, Wojciech Samek:
Deep Learning for Whole-Brain Cognitive Decoding. BCI 2022: 1-3 - [c73]Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin:
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI. CD-MAKE 2022: 1-18 - [c72]Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek:
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. CVPR Workshops 2022: 3366-3375 - [c71]Gerhard Tech, Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Jonathan Pfaff, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
History Dependent Significance Coding for Incremental Neural Network Compression. ICIP 2022: 3541-3545 - [c70]Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek:
FedAUXfdp: Differentially Private One-Shot Federated Distillation. FL@IJCAI 2022: 100-114 - 2021
- [c69]Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek:
Interval Neural Networks as Instability Detectors for Image Reconstructions. Bildverarbeitung für die Medizin 2021: 324-329 - [c68]Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
Encoder Optimizations For The NNR Standard On Neural Network Compression. ICIP 2021: 3522-3526 - 2020
- [c67]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI 2020: 5842-5850 - [c66]Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek:
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CVPR Workshops 2020: 3096-3104 - [c65]Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek:
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CVPR Workshops 2020: 3105-3113 - [c64]Felix Sattler, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
On the Byzantine Robustness of Clustered Federated Learning. ICASSP 2020: 8861-8865 - [c63]David Neumann, Felix Sattler, Heiner Kirchhoffer, Simon Wiedemann, Karsten Müller, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek:
Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates. ICIP 2020: 21-25 - [c62]Paul Haase, Heiko Schwarz, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Arturo Marbán, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
Dependent Scalar Quantization For Neural Network Compression. ICIP 2020: 36-40 - [c61]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML 2020: 3-10 - [c60]Andreas Holzinger, Anna Saranti, Christoph Molnar, Przemyslaw Biecek, Wojciech Samek:
Explainable AI Methods - A Brief Overview. xxAI@ICML 2020: 13-38 - [c59]Grégoire Montavon, Jacob R. Kauffmann, Wojciech Samek, Klaus-Robert Müller:
Explaining the Predictions of Unsupervised Learning Models. xxAI@ICML 2020: 117-138 - [c58]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQ x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. xxAI@ICML 2020: 271-296 - [c57]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. ICPR 2020: 4949-4956 - [c56]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. ICPR 2020: 7609-7616 - [c55]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards Best Practice in Explaining Neural Network Decisions with LRP. IJCNN 2020: 1-7 - 2019
- [c54]Johanna Vielhaben, Hüseyin Camalan, Wojciech Samek, Markus Wenzel:
Viewport Forecasting in 360° Virtual Reality Videos with Machine Learning. AIVR 2019: 74-81 - [c53]Leila Arras, Ahmed Osman, Klaus-Robert Müller, Wojciech Samek:
Evaluating Recurrent Neural Network Explanations. BlackboxNLP@ACL 2019: 113-126 - [c52]Jan Laermann, Wojciech Samek, Nils Strodthoff:
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. GCPR 2019: 360-373 - [c51]Patrick Wagner, Jakob Paul Morath, Arturo Zychlinsky, Klaus-Robert Müller, Wojciech Samek:
Rotation Invariant Clustering of 3D Cell Nuclei Shapes. EMBC 2019: 6022-6027 - [c50]Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. EUSIPCO 2019: 1-5 - [c49]Talmaj Marinc, Vignesh Srinivasan, Serhan Gül, Cornelius Hellge, Wojciech Samek:
Multi-Kernel Prediction Networks for Denoising of Burst Images. ICIP 2019: 2404-2408 - [c48]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. IJCNN 2019: 1-8 - [c47]Simon Wiedemann, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek:
Entropy-Constrained Training of Deep Neural Networks. IJCNN 2019: 1-8 - [c46]Armin W. Thomas, Klaus-Robert Müller, Wojciech Samek:
Deep Transfer Learning for Whole-Brain FMRI Analyses. OR/MLCN@MICCAI 2019: 59-67 - 2018
- [c45]Nils Strodthoff, Baris Göktepe, Thomas Schierl, Wojciech Samek, Cornelius Hellge:
Machine Learning for Early HARQ Feedback Prediction in 5G. GLOBECOM Workshops 2018: 1-6 - [c44]Christopher Ehmann, Wojciech Samek:
Transferring Information Between Neural Networks. ICASSP 2018: 2361-2365 - [c43]Sebastian Bosse, Sören Becker, Zacharias V. Fisches, Wojciech Samek, Thomas Wiegand:
Neural Network-Based Estimation of Distortion Sensitivity for Image Quality Prediction. ICIP 2018: 629-633 - [c42]Arturo Marbán, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals:
Estimation of Interaction Forces in Robotic Surgery using a Semi-Supervised Deep Neural Network Model. IROS 2018: 761-768 - [c41]Sebastian Bosse, Milena T. Bagdasarian, Wojciech Samek, Gabriel Curio, Thomas Wiegand:
On the Stimulation Frequency in SSVEP-based Image Quality Assessment. QoMEX 2018: 1-6 - 2017
- [c40]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller, Alexander Binder:
Object Boundary Detection and Classification with Image-Level Labels. GCPR 2017: 153-164 - [c39]Forooz Shahbazi Avarvand, Sebastian Bosse, Guido Nolte, Thomas Wiegand, Wojciech Samek:
Quality assessment of 3D visualizations with vertical disparity: An ERP approach. EMBC 2017: 4391-4394 - [c38]Forooz Shahbazi Avarvand, Sebastian Bosse, Guido Nolte, Thomas Wiegand, Wojciech Samek:
Measuring the Quality of 3D Visualizations using EEG: a Time-frequency Approach. GBCIC 2017 - [c37]Vignesh Srinivasan, Sebastian Lapuschkin, Cornelius Hellge, Klaus-Robert Müller, Wojciech Samek:
Interpretable human action recognition in compressed domain. ICASSP 2017: 1692-1696 - [c36]Arturo Marbán, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals:
Estimating Position & Velocity in 3D Space from Monocular Video Sequences Using a Deep Neural Network. ICCV Workshops 2017: 1460-1469 - [c35]Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. ICCV Workshops 2017: 1629-1638 - [c34]Sebastian Bosse, Mischa Siekmann, Wojciech Samek, Thomas Wiegand:
A perceptually relevant shearlet-based adaptation of the PSNR. ICIP 2017: 315-319 - [c33]Clemens Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert:
Detection of Face Morphing Attacks by Deep Learning. IWDW 2017: 107-120 - [c32]Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. WASSA@EMNLP 2017: 159-168 - 2016
- [c31]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR 2016: 2912-2920 - [c30]Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Identifying Individual Facial Expressions by Deconstructing a Neural Network. GCPR 2016: 344-354 - [c29]Vignesh Srinivasan, Serhan Gul, Sebastian Bosse, Jan Timo Meyer, Thomas Schierl, Cornelius Hellge, Wojciech Samek:
On the robustness of action recognition methods in compressed and pixel domain. EUVIP 2016: 1-6 - [c28]Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) 2016: 63-71 - [c27]Sebastian Bosse, Qiaobo Chen, Mischa Siekmann, Wojciech Samek, Thomas Wiegand:
Shearlet-based reduced reference image quality assessment. ICIP 2016: 2052-2056 - [c26]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling explanatory heatmap resolution and semantics via decomposition depth. ICIP 2016: 2271-2275 - [c25]Sebastian Bosse, Dominique Maniry, Thomas Wiegand, Wojciech Samek:
A deep neural network for image quality assessment. ICIP 2016: 3773-3777 - [c24]Sebastian Bosse, Mischa Siekmann, Jennifer Rasch, Thomas Wiegand, Wojciech Samek:
Quality assessment of image patches distorted by image compression using crowdsourcing. ICME 2016: 1-6 - [c23]Serhan Gul, Jan Timo Meyer, Cornelius Hellge, Thomas Schierl, Wojciech Samek:
Hybrid video object tracking in H.265/HEVC video streams. MMSP 2016: 1-5 - [c22]Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
Neural network-based full-reference image quality assessment. PCS 2016: 1-5 - [c21]Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Predictions of Non-Linear Classifiers in NLP. Rep4NLP@ACL 2016: 1-7 - [c20]Sebastian Bosse, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
Brain-Computer Interfacing for multimedia quality assessment. SMC 2016: 2834-2839 - [c19]Stephanie Brandl, Klaus-Robert Müller, Wojciech Samek:
Alternative CSP approaches for multimodal distributed BCI data. SMC 2016: 3742-3747 - 2015
- [c18]Stephanie Brandl, Klaus-Robert Müller, Wojciech Samek:
Robust common spatial patterns based on Bhattacharyya distance and Gamma divergence. BCI 2015: 1-4 - [c17]Laura Frølich, Irene Winkler, Klaus-Robert Müller, Wojciech Samek:
Investigating effects of different artefact types on motor imagery BCI. EMBC 2015: 1942-1945 - [c16]Wojciech Samek, Klaus-Robert Müller:
Tackling noise, artifacts and nonstationarity in BCI with robust divergences. EUSIPCO 2015: 2741-2745 - [c15]Stephanie Brandl, Johannes Höhne, Klaus-Robert Müller, Wojciech Samek:
Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment. NER 2015: 224-227 - 2014
- [c14]Wojciech Samek, Klaus-Robert Müller:
Information geometry meets BCI spatial filtering using divergences. BCI 2014: 1-4 - [c13]Wojciech Samek, Motoaki Kawanabe:
Robust common spatial patterns by minimum divergence covariance estimator. ICASSP 2014: 2040-2043 - 2013
- [c12]Wojciech Samek, Alexander Binder, Klaus-Robert Müller:
Multiple Kernel Learning for Brain-Computer Interfacing. EMBC 2013: 7048-7051 - [c11]Wojciech Samek, Duncan A. J. Blythe, Klaus-Robert Müller, Motoaki Kawanabe:
Robust Spatial Filtering with Beta Divergence. NIPS 2013: 1007-1015 - 2012
- [c10]Wojciech Samek, Klaus-Robert Müller, Motoaki Kawanabe, Carmen Vidaurre:
Brain-computer interfacing in discriminative and stationary subspaces. EMBC 2012: 2873-2876 - 2011
- [c9]Wojciech Samek, Alexander Binder, Motoaki Kawanabe:
Multi-task Learning via Non-sparse Multiple Kernel Learning. CAIP (1) 2011: 335-342 - [c8]Alexander Binder, Wojciech Samek, Marius Kloft, Christina Müller, Klaus-Robert Müller, Motoaki Kawanabe:
The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. CLEF (Notebook Papers/Labs/Workshop) 2011 - [c7]Wojciech Wojcikiewicz, Carmen Vidaurre, Motoaki Kawanabe:
Improving Classification Performance of BCIs by Using Stationary Common Spatial Patterns and Unsupervised Bias Adaptation. HAIS (2) 2011: 34-41 - [c6]Motoaki Kawanabe, Wojciech Samek, Paul von Bünau, Frank C. Meinecke:
An Information Geometrical View of Stationary Subspace Analysis. ICANN (2) 2011: 397-404 - [c5]Wojciech Wojcikiewicz, Carmen Vidaurre, Motoaki Kawanabe:
Stationary Common Spatial Patterns: Towards robust classification of non-stationary EEG signals. ICASSP 2011: 577-580 - [c4]Motoaki Kawanabe, Alexander Binder, Christina Müller, Wojciech Wojcikiewicz:
Multi-modal visual concept classification of images via Markov random walk over tags. WACV 2011: 396-401 - 2010
- [c3]Alexander Binder, Wojciech Wojcikiewicz, Christina Müller, Motoaki Kawanabe:
A Hybrid Supervised-Unsupervised Vocabulary Generation Algorithm for Visual Concept Recognition. ACCV (3) 2010: 95-108 - [c2]Wojciech Wojcikiewicz, Alexander Binder, Motoaki Kawanabe:
Shrinking large visual vocabularies using multi-label agglomerative information bottleneck. ICIP 2010: 3849-3852 - [c1]Wojciech Wojcikiewicz, Alexander Binder, Motoaki Kawanabe:
Enhancing Image Classification with Class-wise Clustered Vocabularies. ICPR 2010: 1060-1063
Parts in Books or Collections
- 2019
- [p6]Wojciech Samek, Klaus-Robert Müller:
Towards Explainable Artificial Intelligence. Explainable AI 2019: 5-22 - [p5]Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller:
Layer-Wise Relevance Propagation: An Overview. Explainable AI 2019: 193-209 - [p4]Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek:
Explaining and Interpreting LSTMs. Explainable AI 2019: 211-238 - [p3]Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Understanding Patch-Based Learning of Video Data by Explaining Predictions. Explainable AI 2019: 297-309 - 2014
- [p2]Wojciech Samek:
Über die robuste räumliche Filterung von EEG in nichtstationären Umgebungen. Ausgezeichnete Informatikdissertationen 2014: 251-260 - [p1]Alexander Binder, Wojciech Samek, Klaus-Robert Müller, Motoaki Kawanabe:
Machine Learning for Visual Concept Recognition and Ranking for Images. Towards the Internet of Services 2014: 211-223
Editorship
- 2022
- [e2]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. Lecture Notes in Computer Science 13200, Springer 2022, ISBN 978-3-031-04082-5 [contents] - 2019
- [e1]Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller:
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Lecture Notes in Computer Science 11700, Springer 2019, ISBN 978-3-030-28953-9 [contents]
Data and Artifacts
- 2023
- [d1]Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jérôme Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti:
Data Models for Dataset Drift Controls in Machine Learning With Optical Images - Datasets. Zenodo, 2023
Informal and Other Publications
- 2025
- [i128]Maximilian Dreyer, Jim Berend, Tobias Labarta, Johanna Vielhaben, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek:
Mechanistic understanding and validation of large AI models with SemanticLens. CoRR abs/2501.05398 (2025) - 2024
- [i127]Florian Bley, Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon:
Explaining Predictive Uncertainty by Exposing Second-Order Effects. CoRR abs/2401.17441 (2024) - [i126]Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek:
AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers. CoRR abs/2402.05602 (2024) - [i125]Galip Ümit Yolcu, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
DualView: Data Attribution from the Dual Perspective. CoRR abs/2402.12118 (2024) - [i124]Przemyslaw Biecek, Wojciech Samek:
Explain to Question not to Justify. CoRR abs/2402.13914 (2024) - [i123]Maximilian Dreyer, Erblina Purelku, Johanna Vielhaben, Wojciech Samek, Sebastian Lapuschkin:
PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits. CoRR abs/2404.06453 (2024) - [i122]Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin:
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. CoRR abs/2404.09601 (2024) - [i121]Christian Tinauer, Anna Damulina, Maximilian Sackl, Martin Soellradl, Reduan Achtibat, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Reinhold Schmidt, Stefan Ropele, Wojciech Samek, Christian Langkammer:
Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification. CoRR abs/2404.10433 (2024) - [i120]Leon Witt, Armando Teles Fortes, Kentaroh Toyoda, Wojciech Samek, Dan Li:
Blockchain and Artificial Intelligence: Synergies and Conflicts. CoRR abs/2405.13462 (2024) - [i119]Xiaoyan Yu, Jannik Franzen, Wojciech Samek, Marina M.-C. Höhne, Dagmar Kainmueller:
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models. CoRR abs/2407.03009 (2024) - [i118]Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
The Clever Hans Effect in Unsupervised Learning. CoRR abs/2408.08041 (2024) - [i117]Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers. CoRR abs/2408.12568 (2024) - [i116]Jonas R. Naujoks, Aleksander Krasowski, Moritz Weckbecker, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek, René P. Klausen:
PINNfluence: Influence Functions for Physics-Informed Neural Networks. CoRR abs/2409.08958 (2024) - [i115]Maximilian Andreas Hoefler, Karsten Müller, Wojciech Samek:
XAI-guided Insulator Anomaly Detection for Imbalanced Datasets. CoRR abs/2409.16821 (2024) - [i114]Rohan Reddy Mekala, Frederik Pahde, Simon Baur, Sneha Chandrashekar, Madeline Diep, Markus Wenzel, Eric L. Wisotzky, Galip Ümit Yolcu, Sebastian Lapuschkin, Jackie Ma, Peter Eisert, Mikael Lindvall, Adam A. Porter, Wojciech Samek:
Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization. CoRR abs/2410.05114 (2024) - [i113]Dilyara Bareeva, Galip Ümit Yolcu, Anna Hedström, Niklas Schmolenski, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond. CoRR abs/2410.07158 (2024) - [i112]Michael Detzel, Gabriel Nobis, Jackie Ma, Wojciech Samek:
Spatial Shortcuts in Graph Neural Controlled Differential Equations. CoRR abs/2410.19673 (2024) - [i111]Andreas Lutz, Gabriele Steidl, Karsten Müller, Wojciech Samek:
Optimizing Federated Learning by Entropy-Based Client Selection. CoRR abs/2411.01240 (2024) - [i110]Johanna Vielhaben, Dilyara Bareeva, Jim Berend, Wojciech Samek, Nils Strodthoff:
Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers. CoRR abs/2412.06639 (2024) - [i109]Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon, Thomas Wiegand, Wojciech Samek, Jens Eisert:
Opportunities and limitations of explaining quantum machine learning. CoRR abs/2412.14753 (2024) - 2023
- [i108]Anna Hedström, Philine Lou Bommer, Kristoffer K. Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. CoRR abs/2302.07265 (2023) - [i107]David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek:
A Privacy Preserving System for Movie Recommendations using Federated Learning. CoRR abs/2303.04689 (2023) - [i106]Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek:
Explainable AI for Time Series via Virtual Inspection Layers. CoRR abs/2303.06365 (2023) - [i105]Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. CoRR abs/2303.12641 (2023) - [i104]Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin, Wojciech Samek, Johanna Vielhaben:
XAI-based Comparison of Input Representations for Audio Event Classification. CoRR abs/2304.14019 (2023) - [i103]Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed M. Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala:
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. CoRR abs/2306.13384 (2023) - [i102]Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin:
From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space. CoRR abs/2308.09437 (2023) - [i101]Leander Weber, Jim Berend, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Layer-wise Feedback Propagation. CoRR abs/2308.12053 (2023) - [i100]Karam Dawoud, Wojciech Samek, Peter Eisert, Sebastian Lapuschkin, Sebastian Bosse:
Human-Centered Evaluation of XAI Methods. CoRR abs/2310.07534 (2023) - [i99]Gabriel Nobis, Marco Aversa, Maximilian Springenberg, Michael Detzel, Stefano Ermon, Shinichi Nakajima, Roderick Murray-Smith, Sebastian Lapuschkin, Christoph Knochenhauer, Luis Oala, Wojciech Samek:
Generative Fractional Diffusion Models. CoRR abs/2310.17638 (2023) - [i98]Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf:
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions. CoRR abs/2310.19775 (2023) - [i97]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - [i96]Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin:
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. CoRR abs/2311.16681 (2023) - 2022
- [i95]Frederik Pahde, Leander Weber, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin:
PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging. CoRR abs/2202.03482 (2022) - [i94]Anna Hedström, Leander Weber, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations. CoRR abs/2202.06861 (2022) - [i93]Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement. CoRR abs/2203.08008 (2022) - [i92]Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek:
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. CoRR abs/2204.04424 (2022) - [i91]Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin:
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI. CoRR abs/2205.01929 (2022) - [i90]Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li:
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. CoRR abs/2205.07855 (2022) - [i89]Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek:
FedAUXfdp: Differentially Private One-Shot Federated Distillation. CoRR abs/2205.14960 (2022) - [i88]Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation. CoRR abs/2206.03208 (2022) - [i87]Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jérôme Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti:
Data Models for Dataset Drift Controls in Machine Learning With Images. CoRR abs/2211.02578 (2022) - [i86]Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. CoRR abs/2211.11426 (2022) - [i85]Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR abs/2211.12486 (2022) - [i84]Fabian Horst, Djordje Slijepcevic, Matthias Zeppelzauer, Anna-Maria Raberger, Sebastian Lapuschkin, Wojciech Samek, Wolfgang Immanuel Schöllhorn, Christian Breiteneder, Brian Horsak:
Explaining automated gender classification of human gait. CoRR abs/2211.17015 (2022) - [i83]Djordje Slijepcevic, Fabian Horst, Marvin Simak, Sebastian Lapuschkin, Anna-Maria Raberger, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer, Brian Horsak:
Explaining machine learning models for age classification in human gait analysis. CoRR abs/2211.17016 (2022) - [i82]Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Optimizing Explanations by Network Canonization and Hyperparameter Search. CoRR abs/2211.17174 (2022) - 2021
- [i81]Felix Sattler, Tim Korjakow, Roman Rischke, Wojciech Samek:
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning. CoRR abs/2102.02514 (2021) - [i80]Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. CoRR abs/2106.13200 (2021) - [i79]Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. CoRR abs/2106.13497 (2021) - [i78]Leon Witt, Usama Zafar, KuoYeh Shen, Felix Sattler, Dan Li, Wojciech Samek:
Reward-Based 1-bit Compressed Federated Distillation on Blockchain. CoRR abs/2106.14265 (2021) - [i77]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. CoRR abs/2109.04236 (2021) - [i76]Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller:
Evaluating deep transfer learning for whole-brain cognitive decoding. CoRR abs/2111.01562 (2021) - [i75]Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Toward Explainable AI for Regression Models. CoRR abs/2112.11407 (2021) - 2020
- [i74]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Understanding Image Captioning Models beyond Visualizing Attention. CoRR abs/2001.01037 (2020) - [i73]Felix Sattler, Thomas Wiegand, Wojciech Samek:
Trends and Advancements in Deep Neural Network Communication. CoRR abs/2003.03320 (2020) - [i72]Ahmed Osman, Leila Arras, Wojciech Samek:
Towards Ground Truth Evaluation of Visual Explanations. CoRR abs/2003.07258 (2020) - [i71]Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller:
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR abs/2003.07631 (2020) - [i70]Luis Oala, Cosmas Heiss, Jan MacDonald, Maximilian März, Wojciech Samek, Gitta Kutyniok:
Interval Neural Networks: Uncertainty Scores. CoRR abs/2003.11566 (2020) - [i69]Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek:
Interval Neural Networks as Instability Detectors for Image Reconstructions. CoRR abs/2003.13471 (2020) - [i68]Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek:
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CoRR abs/2004.01077 (2020) - [i67]Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek:
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CoRR abs/2004.04729 (2020) - [i66]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. CoRR abs/2004.10484 (2020) - [i65]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand:
Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements. CoRR abs/2004.11841 (2020) - [i64]Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek:
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. CoRR abs/2004.13701 (2020) - [i63]Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello:
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures. CoRR abs/2006.07767 (2020) - [i62]Anko Börner, Heinz-Wilhelm Hübers, Odej Kao, Florian Schmidt, Soeren Becker, Joachim Denzler, Daniel Matolin, David Haber, Sergio Lucia, Wojciech Samek, Rudolph Triebel, Sascha Eichstädt, Felix Bießmann, Anna M. Kruspe, Peter Jung, Manon Kok, Guillermo Gallego, Ralf Berger:
Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. CoRR abs/2006.08368 (2020) - [i61]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. CoRR abs/2007.08790 (2020) - [i60]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Langevin Cooling for Domain Translation. CoRR abs/2008.13723 (2020) - [i59]Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller:
A Unifying Review of Deep and Shallow Anomaly Detection. CoRR abs/2009.11732 (2020) - [i58]Felix Sattler, Arturo Marbán, Roman Rischke, Wojciech Samek:
Communication-Efficient Federated Distillation. CoRR abs/2012.00632 (2020) - [i57]Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann, Daniel Becking, Wojciech Samek, Friedel Gerfers, Thomas Wiegand:
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons. CoRR abs/2012.11331 (2020) - 2019
- [i56]Talmaj Marinc, Vignesh Srinivasan, Serhan Gül, Cornelius Hellge, Wojciech Samek:
Multi-Kernel Prediction Networks for Denoising of Burst Images. CoRR abs/1902.05392 (2019) - [i55]Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR abs/1902.10178 (2019) - [i54]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Robust and Communication-Efficient Federated Learning from Non-IID Data. CoRR abs/1903.02891 (2019) - [i53]Kim Nicoli, Pan Kessel, Nils Strodthoff, Wojciech Samek, Klaus-Robert Müller, Shinichi Nakajima:
Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling. CoRR abs/1903.11048 (2019) - [i52]Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. CoRR abs/1904.05586 (2019) - [i51]Leila Arras, Ahmed Osman, Klaus-Robert Müller, Wojciech Samek:
Evaluating Recurrent Neural Network Explanations. CoRR abs/1904.11829 (2019) - [i50]Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Ahmed Osman, Detlev Marpe, Heiko Schwarz, Thomas Wiegand, Wojciech Samek:
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression. CoRR abs/1905.08318 (2019) - [i49]Jan Laermann, Wojciech Samek, Nils Strodthoff:
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. CoRR abs/1906.00735 (2019) - [i48]Jacob R. Kauffmann, Malte Esders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
From Clustering to Cluster Explanations via Neural Networks. CoRR abs/1906.07633 (2019) - [i47]Armin W. Thomas, Klaus-Robert Müller, Wojciech Samek:
Deep Transfer Learning For Whole-Brain fMRI Analyses. CoRR abs/1907.01953 (2019) - [i46]Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Detlev Marpe, Heiko Schwarz, Thomas Wiegand, Wojciech Samek:
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. CoRR abs/1907.11900 (2019) - [i45]Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder:
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. CoRR abs/1908.06943 (2019) - [i44]Wojciech Samek, Klaus-Robert Müller:
Towards Explainable Artificial Intelligence. CoRR abs/1909.12072 (2019) - [i43]Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek:
Explaining and Interpreting LSTMs. CoRR abs/1909.12114 (2019) - [i42]Felix Sattler, Klaus-Robert Müller, Wojciech Samek:
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints. CoRR abs/1910.01991 (2019) - [i41]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards best practice in explaining neural network decisions with LRP. CoRR abs/1910.09840 (2019) - [i40]Kim A. Nicoli, Shinichi Nakajima, Nils Strodthoff, Wojciech Samek, Klaus-Robert Müller, Pan Kessel:
Asymptotically Unbiased Generative Neural Sampling. CoRR abs/1910.13496 (2019) - [i39]Fabian Horst, Djordje Slijepcevic, Sebastian Lapuschkin, Anna-Maria Raberger, Matthias Zeppelzauer, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Brian Horsak:
On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence. CoRR abs/1912.07737 (2019) - [i38]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. CoRR abs/1912.08881 (2019) - [i37]Christopher J. Anders, Talmaj Marinc, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. CoRR abs/1912.11425 (2019) - 2018
- [i36]Ahmed Osman, Wojciech Samek:
Dual Recurrent Attention Units for Visual Question Answering. CoRR abs/1802.00209 (2018) - [i35]Arturo Marbán, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals:
A Recurrent Convolutional Neural Network Approach for Sensorless Force Estimation in Robotic Surgery. CoRR abs/1805.08545 (2018) - [i34]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. CoRR abs/1805.08768 (2018) - [i33]Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Compact and Computationally Efficient Representation of Deep Neural Networks. CoRR abs/1805.10692 (2018) - [i32]Vignesh Srinivasan, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Counterstrike: Defending Deep Learning Architectures Against Adversarial Samples by Langevin Dynamics with Supervised Denoising Autoencoder. CoRR abs/1805.12017 (2018) - [i31]Clemens Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert:
Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks. CoRR abs/1806.04265 (2018) - [i30]Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Understanding Patch-Based Learning by Explaining Predictions. CoRR abs/1806.06926 (2018) - [i29]Sören Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. CoRR abs/1807.03418 (2018) - [i28]Nils Strodthoff, Baris Göktepe, Thomas Schierl, Cornelius Hellge, Wojciech Samek:
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. CoRR abs/1807.10495 (2018) - [i27]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate neural networks! CoRR abs/1808.04260 (2018) - [i26]Fabian Horst, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller, Wolfgang Immanuel Schöllhorn:
What is Unique in Individual Gait Patterns? Understanding and Interpreting Deep Learning in Gait Analysis. CoRR abs/1808.04308 (2018) - [i25]Armin W. Thomas, Hauke R. Heekeren, Klaus-Robert Müller, Wojciech Samek:
Interpretable LSTMs For Whole-Brain Neuroimaging Analyses. CoRR abs/1810.09945 (2018) - [i24]Tatiana A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan:
Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. CoRR abs/1811.04602 (2018) - [i23]Simon Wiedemann, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek:
Entropy-Constrained Training of Deep Neural Networks. CoRR abs/1812.07520 (2018) - 2017
- [i22]Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Recurrent Neural Network Predictions in Sentiment Analysis. CoRR abs/1706.07206 (2017) - [i21]Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Methods for Interpreting and Understanding Deep Neural Networks. CoRR abs/1706.07979 (2017) - [i20]Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Exploring text datasets by visualizing relevant words. CoRR abs/1707.05261 (2017) - [i19]Franziska Horn, Leila Arras, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Discovering topics in text datasets by visualizing relevant words. CoRR abs/1707.06100 (2017) - [i18]Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. CoRR abs/1708.07689 (2017) - [i17]Wojciech Samek, Thomas Wiegand, Klaus-Robert Müller:
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models. CoRR abs/1708.08296 (2017) - [i16]Wojciech Samek, Slawomir Stanczak, Thomas Wiegand:
The Convergence of Machine Learning and Communications. CoRR abs/1708.08299 (2017) - 2016
- [i15]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth. CoRR abs/1603.06463 (2016) - [i14]Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek:
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR abs/1604.00825 (2016) - [i13]Irene Sturm, Sebastian Bach, Wojciech Samek, Klaus-Robert Müller:
Interpretable Deep Neural Networks for Single-Trial EEG Classification. CoRR abs/1604.08201 (2016) - [i12]Farhad Arbabzadah, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Identifying individual facial expressions by deconstructing a neural network. CoRR abs/1606.07285 (2016) - [i11]Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Explaining Predictions of Non-Linear Classifiers in NLP. CoRR abs/1606.07298 (2016) - [i10]Jing Yu Koh, Wojciech Samek, Klaus-Robert Müller, Alexander Binder:
Zero Shot Learning for Semantic Boundary Detection - How Far Can We Get? CoRR abs/1606.09187 (2016) - [i9]Wikor Pronobis, Danny Panknin, Johannes Kirschnick, Vignesh Srinivasan, Wojciech Samek, Volker Markl, Manohar Kaul, Klaus-Robert Müller, Shinichi Nakajima:
Sharing Hash Codes for Multiple Purposes. CoRR abs/1609.03219 (2016) - [i8]Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR abs/1611.08191 (2016) - [i7]Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment. CoRR abs/1612.01697 (2016) - [i6]Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach. CoRR abs/1612.07843 (2016) - 2015
- [i5]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller:
Evaluating the visualization of what a Deep Neural Network has learned. CoRR abs/1509.06321 (2015) - [i4]Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR abs/1512.00172 (2015) - [i3]Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR abs/1512.02479 (2015) - 2012
- [i2]Wojciech Samek, Frank C. Meinecke, Klaus-Robert Müller:
Transferring Subspaces Between Subjects in Brain-Computer Interfacing. CoRR abs/1209.4115 (2012) - 2011
- [i1]Alexander Binder, Shinichi Nakajima, Marius Kloft, Christina Müller, Wojciech Samek, Ulf Brefeld, Klaus-Robert Müller, Motoaki Kawanabe:
Insights from Classifying Visual Concepts with Multiple Kernel Learning. CoRR abs/1112.3697 (2011)
Coauthor Index
Sebastian Lapuschkin
aka: Sebastian Bach
aka: Sebastian Bach
[j65] [j63] [j62] [j58] [j55] [j54] [j52] [j48] [j47] [j46] [j43] [j35] [j33] [j17] [j10] [j9] [j7] [c89] [c88] [c87] [c86] [c84] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c73] [c58] [c57] [c56] [c55] [c37] [c35] [c31] [c28] [c26] [p5] [i128] [i127] [i126] [i125] [i123] [i122] [i121] [i117] [i116] [i114] [i113] [i108] [i106] [i105] [i104] [i102] [i101] [i100] [i99] [i96] [i95] [i94] [i93] [i91] [i88] [i86] [i85] [i84] [i83] [i82] [i80] [i77] [i74] [i71] [i66] [i61] [i55] [i45] [i41] [i39] [i38] [i37] [i29] [i27] [i26] [i18] [i15] [i14] [i13] [i8] [i5] [i4] [i3]
[j63] [j60] [j56] [j49] [j46] [j43] [j42] [j37] [j35] [j34] [j33] [j31] [j25] [j24] [j23] [j19] [j17] [j15] [j14] [j12] [j11] [j10] [j9] [j7] [j6] [j5] [j4] [j3] [j2] [j1] [c78] [c74] [c67] [c64] [c61] [c59] [c53] [c51] [c50] [c48] [c47] [c46] [c40] [c37] [c35] [c32] [c31] [c30] [c28] [c26] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c12] [c11] [c10] [c8] [p6] [p5] [p4] [p3] [p1] [e2] [e1] [i118] [i85] [i80] [i79] [i76] [i75] [i71] [i65] [i60] [i59] [i55] [i54] [i53] [i52] [i51] [i48] [i47] [i45] [i44] [i43] [i42] [i40] [i38] [i37] [i34] [i33] [i32] [i30] [i29] [i27] [i26] [i25] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [i2] [i1]
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