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ORCIDSepp Hochreiter
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- affiliation: Johannes Kepler University of Linz, Austria
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2020 – today
- 2024
[j31]Emma Svensson
, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer:
HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions. J. Chem. Inf. Model. 64(7): 2539-2553 (2024)- [c57]Johannes Lehner, Benedikt Alkin, Andreas Fürst, Elisabeth Rumetshofer, Lukas Miklautz, Sepp Hochreiter:
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget. AAAI 2024: 2965-2973 - [c56]Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger:
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization. ICML 2024 - [c55]Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner:
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization. ICML 2024 - [c54]Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
xLSTM: Extended Long Short-Term Memory. NeurIPS 2024 - [c53]Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter:
Energy-based Hopfield Boosting for Out-of-Distribution Detection. NeurIPS 2024 - [i77]Marius-Constantin Dinu, Claudiu Leoveanu-Condrei, Markus Holzleitner, Werner Zellinger, Sepp Hochreiter:
SymbolicAI: A framework for logic-based approaches combining generative models and solvers. CoRR abs/2402.00854 (2024) - [i76]Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter:
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations. CoRR abs/2402.10093 (2024) - [i75]Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger:
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization. CoRR abs/2402.13891 (2024) - [i74]Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter:
Geometry-Informed Neural Networks. CoRR abs/2402.14009 (2024) - [i73]Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer:
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification. CoRR abs/2404.07194 (2024) - [i72]Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
xLSTM: Extended Long Short-Term Memory. CoRR abs/2405.04517 (2024) - [i71]Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter:
Energy-based Hopfield Boosting for Out-of-Distribution Detection. CoRR abs/2405.08766 (2024) - [i70]Ajay Patel, Markus Hofmarcher, Claudiu Leoveanu-Condrei, Marius-Constantin Dinu, Chris Callison-Burch, Sepp Hochreiter:
Large Language Models Can Self-Improve At Web Agent Tasks. CoRR abs/2405.20309 (2024) - [i69]Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner:
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization. CoRR abs/2406.01661 (2024) - [i68]Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter:
Vision-LSTM: xLSTM as Generic Vision Backbone. CoRR abs/2406.04303 (2024) - [i67]Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter:
Semantically Diverse Language Generation for Uncertainty Estimation in Language Models. CoRR abs/2406.04306 (2024) - [i66]Wei Lin, Muhammad Jehanzeb Mirza, Sivan Doveh, Rogério Feris, Raja Giryes, Sepp Hochreiter, Leonid Karlinsky:
Comparison Visual Instruction Tuning. CoRR abs/2406.09240 (2024) - [i65]Vihang Patil, Markus Hofmarcher, Elisabeth Rumetshofer, Sepp Hochreiter:
Contrastive Abstraction for Reinforcement Learning. CoRR abs/2410.00704 (2024) - [i64]Vihang Patil, Andreas Radler, Daniel Klotz, Sepp Hochreiter:
Simplified priors for Object-Centric Learning. CoRR abs/2410.00728 (2024) - [i63]Thomas Schmied, Fabian Paischer, Vihang Patil, Markus Hofmarcher, Razvan Pascanu, Sepp Hochreiter:
Retrieval-Augmented Decision Transformer: External Memory for In-context RL. CoRR abs/2410.07071 (2024) - [i62]Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter:
One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation. CoRR abs/2410.07170 (2024) - [i61]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter:
On Information-Theoretic Measures of Predictive Uncertainty. CoRR abs/2410.10786 (2024) - [i60]Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter, Nuria Oliver:
The Disparate Benefits of Deep Ensembles. CoRR abs/2410.13831 (2024) - [i59]Thomas Schmied, Thomas Adler, Vihang Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter:
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks. CoRR abs/2410.22391 (2024) - [i58]Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer:
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. CoRR abs/2411.04165 (2024) - [i57]Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter:
FlashRNN: Optimizing Traditional RNNs on Modern Hardware. CoRR abs/2412.07752 (2024) - [i56]Lukas Aichberger, Kajetan Schweighofer, Sepp Hochreiter:
Rethinking Uncertainty Estimation in Natural Language Generation. CoRR abs/2412.15176 (2024) - 2023
- [j30]Lorenzo Servadei, Jin Hwa Lee, José Antonio Arjona-Medina, Michael Werner, Sepp Hochreiter, Wolfgang Ecker, Robert Wille:
Deep Reinforcement Learning for Optimization at Early Design Stages. IEEE Des. Test 40(1): 43-51 (2023) - [j29]Yonghao Xu, Weikang Yu, Pedram Ghamisi, Michael Kopp, Sepp Hochreiter:
Txt2Img-MHN: Remote Sensing Image Generation From Text Using Modern Hopfield Networks. IEEE Trans. Image Process. 32: 5737-5750 (2023) - [c52]Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter:
Boundary Graph Neural Networks for 3D Simulations. AAAI 2023: 9099-9107 - [c51]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. ICLR 2023 - [c50]Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer:
Context-enriched molecule representations improve few-shot drug discovery. ICLR 2023 - [c49]Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer:
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. ICML 2023: 30458-30490 - [c48]Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter:
Conformal Prediction for Time Series with Modern Hopfield Networks. NeurIPS 2023 - [c47]Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter:
Semantic HELM: A Human-Readable Memory for Reinforcement Learning. NeurIPS 2023 - [c46]Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner:
Variational Annealing on Graphs for Combinatorial Optimization. NeurIPS 2023 - [c45]Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter:
Learning to Modulate pre-trained Models in RL. NeurIPS 2023 - [c44]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter:
Quantification of Uncertainty with Adversarial Models. NeurIPS 2023 - [i55]Bernhard Schäfl, Lukas Gruber, Johannes Brandstetter, Sepp Hochreiter:
G-Signatures: Global Graph Propagation With Randomized Signatures. CoRR abs/2302.08811 (2023) - [i54]Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer:
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. CoRR abs/2303.03363 (2023) - [i53]Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2022 - Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. CoRR abs/2303.07758 (2023) - [i52]Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter:
Conformal Prediction for Time Series with Modern Hopfield Networks. CoRR abs/2303.12783 (2023) - [i51]Johannes Lehner, Benedikt Alkin, Andreas Fürst, Elisabeth Rumetshofer, Lukas Miklautz, Sepp Hochreiter:
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget. CoRR abs/2304.10520 (2023) - [i50]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. CoRR abs/2305.01281 (2023) - [i49]Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer:
Context-enriched molecule representations improve few-shot drug discovery. CoRR abs/2305.09481 (2023) - [i48]Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter:
Semantic HELM: An Interpretable Memory for Reinforcement Learning. CoRR abs/2306.09312 (2023) - [i47]Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter:
Learning to Modulate pre-trained Models in RL. CoRR abs/2306.14884 (2023) - [i46]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter:
Quantification of Uncertainty with Adversarial Models. CoRR abs/2307.03217 (2023) - [i45]Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter:
SITTA: A Semantic Image-Text Alignment for Image Captioning. CoRR abs/2307.05591 (2023) - [i44]Bernhard Nessler, Thomas Doms, Sepp Hochreiter:
Functional trustworthiness of AI systems by statistically valid testing. CoRR abs/2310.02727 (2023) - [i43]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter:
Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty. CoRR abs/2311.08309 (2023) - [i42]Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner:
Variational Annealing on Graphs for Combinatorial Optimization. CoRR abs/2311.14156 (2023) - 2022
- [j28]Sepp Hochreiter:
Toward a broad AI. Commun. ACM 65(4): 56-57 (2022) - [j27]Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer:
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. J. Chem. Inf. Model. 62(9): 2111-2120 (2022) - [j26]Theresa Roland, Carl Böck, Thomas Tschoellitsch, Alexander Maletzky, Sepp Hochreiter, Jens Meier, Günter Klambauer:
Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. J. Medical Syst. 46(5): 23 (2022) - [j25]Philippe A. Robert, Rahmad Akbar, Robert Frank, Milena Pavlovic, Michael Widrich, Igor Snapkov, Andrei Slabodkin, Maria Chernigovskaya, Lonneke Scheffer, Eva Smorodina, Puneet Rawat, Brij Bhushan Mehta, Mai Ha Vu, Ingvild Frøberg Mathisen, Aurél Prósz, Krzysztof Abram, Alex Olar, Enkelejda Miho, Dag Trygve Truslew Haug, Fridtjof Lund-Johansen, Sepp Hochreiter, Ingrid Hobæk Haff, Günter Klambauer, Geir Kjetil Sandve, Victor Greiff:
Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. Nat. Comput. Sci. 2(12): 845-865 (2022) - [c43]Pedram Ghamisi, Omid Ghorbanzadeh, Yonghao Xu, Pedro Herruzo, David P. Kreil, Michael Kopp, Sepp Hochreiter:
The Landslide4Sense Competition 2022. CDCEO@IJCAI 2022: 91 - [c42]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope With Non-Stationarity in Lifelong Reinforcement Learning. CoLLAs 2022: 441-469 - [c41]Kajetan Schweighofer, Marius-Constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
A Dataset Perspective on Offline Reinforcement Learning. CoLLAs 2022: 470-517 - [c40]Martin Gauch, Maximilian Beck, Thomas Adler, Dmytro Kotsur, Stefan Fiel, Hamid Eghbal-zadeh, Johannes Brandstetter, Johannes Kofler, Markus Holzleitner, Werner Zellinger, Daniel Klotz, Sepp Hochreiter, Sebastian Lehner:
Few-Shot Learning by Dimensionality Reduction in Gradient Space. CoLLAs 2022: 1043-1064 - [c39]Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-Zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. ICML 2022: 17156-17185 - [c38]Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, José Antonio Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. ICML 2022: 17531-17572 - [c37]Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner, Viet T. Tran, Fei Tang, Hubert Ramsauer, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto, Sepp Hochreiter:
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. NeurIPS 2022 - [i41]Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. CoRR abs/2203.17070 (2022) - [i40]Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. CoRR abs/2205.12258 (2022) - [i39]Bernhard Schäfl, Lukas Gruber, Angela Bitto-Nemling, Sepp Hochreiter:
Hopular: Modern Hopfield Networks for Tabular Data. CoRR abs/2206.00664 (2022) - [i38]Mathias Lechner, Ramin M. Hasani, Zahra Babaiee, Radu Grosu, Daniela Rus, Thomas A. Henzinger, Sepp Hochreiter:
Entangled Residual Mappings. CoRR abs/2206.01261 (2022) - [i37]Martin Gauch, Maximilian Beck, Thomas Adler, Dmytro Kotsur, Stefan Fiel, Hamid Eghbal-zadeh, Johannes Brandstetter, Johannes Kofler, Markus Holzleitner, Werner Zellinger, Daniel Klotz, Sepp Hochreiter, Sebastian Lehner:
Few-Shot Learning by Dimensionality Reduction in Gradient Space. CoRR abs/2206.03483 (2022) - [i36]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning. CoRR abs/2207.05742 (2022) - [i35]Yonghao Xu, Weikang Yu, Pedram Ghamisi, Michael Kopp, Sepp Hochreiter:
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks. CoRR abs/2208.04441 (2022) - 2021
- [j24]Andreu Vall, Yogesh Sabnis, Jiye Shi, Reiner Class, Sepp Hochreiter, Günter Klambauer:
The Promise of AI for DILI Prediction. Frontiers Artif. Intell. 4: 638410 (2021) - [j23]Markus Holzleitner, Lukas Gruber, José Antonio Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter:
Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. Trans. Large Scale Data Knowl. Centered Syst. 48: 105-130 (2021) - [c36]Pedro Herruzo, Aleksandra Gruca, Llorenç Lliso, Xavier Calbet, Pilar Rípodas, Sepp Hochreiter, Michael Kopp, David P. Kreil:
High-resolution multi-channel weather forecasting - First insights on transfer learning from the Weather4cast Competitions 2021. IEEE BigData 2021: 5750-5757 - [c35]Aleksandra Gruca, Pedro Herruzo, Pilar Rípodas, Andrzej Kucik, Christian Briese, Michael K. Kopp, Sepp Hochreiter, Pedram Ghamisi, David P. Kreil:
CDCEO'21 - First Workshop on Complex Data Challenges in Earth Observation. CIKM 2021: 4878-4879 - [c34]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David P. Kreil, Michael K. Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. ICLR 2021 - [c33]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. ICML 2021: 4275-4286 - [c32]Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. NeurIPS (Competition and Demos) 2021: 97-112 - [c31]Vittorio Caggiano, Guillaume Durandau, Huawei Wang, Alberto Silvio Chiappa, Alexander Mathis, Pablo Tano, Nisheet Patel, Alexandre Pouget, Pierre Schumacher, Georg Martius, Daniel F. B. Haeufle, Yiran Geng, Boshi An, Yifan Zhong, Jiaming Ji, Yuanpei Chen, Hao Dong, Yaodong Yang, Rahul Siripurapu, Luis Eduardo Ferro Diez, Michael Kopp, Vihang Patil, Sepp Hochreiter, Yuval Tassa, Josh Merel, Randy Schultheis, Seungmoon Song, Massimo Sartori, Vikash Kumar:
MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand. NeurIPS (Competition and Demos) 2021: 233-250 - [c30]Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. NeurIPS (Competition and Demos) 2021: 251-278 - [c29]Aleksandra Gruca, Federico Serva, Llorenç Lliso, Pilar Rípodas, Xavier Calbet, Pedro Herruzo, Jirí Pihrt, Rudolf Raevskiy, Petr Simánek, Matej Choma, Yang Li, Haiyu Dong, Yury Belousov, Sergey Polezhaev, Brian Pulfer, Minseok Seo, Doyi Kim, Seungheon Shin, Eunbin Kim, Sewoong Ahn, Yeji Choi, Jinyoung Park, Minseok Son, Seungju Cho, Inyoung Lee, Changick Kim, Taehyeon Kim, Shinhwan Kang, Hyeonjeong Shin, Deukryeol Yoon, Seongha Eom, Kijung Shin, Se-Young Yun, Bertrand Le Saux, Michael K. Kopp, Sepp Hochreiter, David P. Kreil:
Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. NeurIPS (Competition and Demos) 2021: 292-313 - [i34]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. CoRR abs/2101.05186 (2021) - [i33]Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler:
Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications. CoRR abs/2103.16910 (2021) - [i32]Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. CoRR abs/2104.03279 (2021) - [i31]Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter:
Learning 3D Granular Flow Simulations. CoRR abs/2105.01636 (2021) - [i30]Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter:
Boundary Graph Neural Networks for 3D Simulations. CoRR abs/2106.11299 (2021) - [i29]Andreas Fürst, Elisabeth Rumetshofer, Viet Tran, Hubert Ramsauer, Fei Tang, Johannes Lehner, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto-Nemling, Sepp Hochreiter:
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. CoRR abs/2110.11316 (2021) - [i28]Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter:
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. CoRR abs/2111.04714 (2021) - 2020
- [j22]Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen:
Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics 12(1): 26 (2020) - [c28]Marius-Constantin Dinu, Markus Hofmarcher, Vihang Prakash Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
XAI and Strategy Extraction via Reward Redistribution. xxAI@ICML 2020: 177-205 - [c27]Lorenzo Servadei, Jiapeng Zheng, Jose A. Arjona-Medina, Michael Werner, Volkan Esen, Sepp Hochreiter, Wolfgang Ecker, Robert Wille:
Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning. MLCAD 2020: 37-42 - [c26]Michael Kopp, David P. Kreil, Moritz Neun, David Jonietz, Henry Martin, Pedro Herruzo, Aleksandra Gruca, Ali Soleymani, Fanyou Wu, Yang Liu, Jingwei Xu, Jianjin Zhang, Jay Santokhi, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Pak Hay Kwok, Qi Qi, Sepp Hochreiter:
Traffic4cast at NeurIPS 2020 ? yet more on theunreasonable effectiveness of gridded geo-spatial processes. NeurIPS (Competition and Demos) 2020: 325-343 - [c25]Michael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. NeurIPS 2020 - [i27]Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch, Philipp Renz, Johannes Schimunek, Philipp Seidl, Andreu Vall, Michael Widrich, Sepp Hochreiter, Günter Klambauer:
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks. CoRR abs/2004.00979 (2020) - [i26]Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlovic, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. CoRR abs/2007.13505 (2020) - [i25]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Milena Pavlovic, Geir Kjetil Sandve, Victor Greiff, David P. Kreil, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. CoRR abs/2008.02217 (2020) - [i24]Vihang Prakash Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. CoRR abs/2009.14108 (2020) - [i23]Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David P. Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter:
Cross-Domain Few-Shot Learning by Representation Fusion. CoRR abs/2010.06498 (2020) - [i22]Martin Gauch, Frederik Kratzert, Daniel Klotz, Grey Nearing, Jimmy Lin, Sepp Hochreiter:
Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network. CoRR abs/2010.07921 (2020) - [i21]Markus Holzleitner, Lukas Gruber, Jose A. Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter:
Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. CoRR abs/2012.01399 (2020) - [i20]Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. CoRR abs/2012.14295 (2020)
2010 – 2019
- 2019
- [j21]Günter Klambauer, Sepp Hochreiter, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 59(3): 945-946 (2019) - [j20]Markus Hofmarcher, Elisabeth Rumetshofer, Djork-Arné Clevert, Sepp Hochreiter, Günter Klambauer:
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks. J. Chem. Inf. Model. 59(3): 1163-1171 (2019) - [c24]Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl, Sepp Hochreiter, Günter Klambauer:
Human-level Protein Localization with Convolutional Neural Networks. ICLR (Poster) 2019 - [c23]David P. Kreil, Michael K. Kopp, David Jonietz, Moritz Neun, Aleksandra Gruca, Pedro Herruzo, Henry Martin, Ali Soleymani, Sepp Hochreiter:
The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task - Insights from the IARAI Traffic4cast Competition at NeurIPS 2019. NeurIPS (Competition and Demos) 2019: 232-241 - [c22]Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter:
RUDDER: Return Decomposition for Delayed Rewards. NeurIPS 2019: 13544-13555 - [p6]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 - [p5]Markus Hofmarcher, Thomas Unterthiner, Jose A. Arjona-Medina, Günter Klambauer, Sepp Hochreiter, Bernhard Nessler:
Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. Explainable AI 2019: 285-296 - [p4]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. Explainable AI 2019: 331-345 - [p3]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. Explainable AI 2019: 347-362 - [i19]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. CoRR abs/1903.02788 (2019) - [i18]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. CoRR abs/1903.07903 (2019) - [i17]Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling. CoRR abs/1907.08456 (2019) - [i16]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) - [i15]Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter:
Patch Refinement - Localized 3D Object Detection. CoRR abs/1910.04093 (2019) - [i14]Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter:
Quantum Optical Experiments Modeled by Long Short-Term Memory. CoRR abs/1910.13804 (2019) - [i13]Frederik Kratzert, Daniel Klotz, Johannes Brandstetter, Pieter-Jan Hoedt, Grey Nearing, Sepp Hochreiter:
Using LSTMs for climate change assessment studies on droughts and floods. CoRR abs/1911.03941 (2019) - [i12]Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher, Philipp Tschandl, Harald Kittler, Sepp Hochreiter, Wolfram Hötzenecker, Günter Klambauer:
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. CoRR abs/1911.06616 (2019) - 2018
- [j19]Kristina Preuer, Richard P. I. Lewis, Sepp Hochreiter, Andreas Bender, Krishna C. Bulusu, Günter Klambauer:
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning. Bioinform. 34(9): 1538-1546 (2018) - [j18]Sepp Hochreiter, Günter Klambauer, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 58(9): 1723-1724 (2018) - [j17]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery. J. Chem. Inf. Model. 58(9): 1736-1741 (2018) - [c21]Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. ICLR (Poster) 2018 - [c20]Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter:
First Order Generative Adversarial Networks. ICML 2018: 4574-4583 - [i11]Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter:
First Order Generative Adversarial Networks. CoRR abs/1802.04591 (2018) - [i10]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemblNet Distance: A metric for generative models for molecules. CoRR abs/1803.09518 (2018) - [i9]Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Sepp Hochreiter:
RUDDER: Return Decomposition for Delayed Rewards. CoRR abs/1806.07857 (2018) - 2017
- [j16]Djork-Arné Clevert, Thomas Unterthiner, Gundula Povysil, Sepp Hochreiter:
Rectified factor networks for biclustering of omics data. Bioinform. 33(14): i59-i66 (2017) - [c19]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. NIPS 2017: 971-980 - [c18]Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter:
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. NIPS 2017: 6626-6637 - [i8]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. CoRR abs/1706.02515 (2017) - [i7]Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Sepp Hochreiter:
GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium. CoRR abs/1706.08500 (2017) - [i6]Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. CoRR abs/1708.08819 (2017) - 2016
- [c17]Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter:
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). ICLR (Poster) 2016 - 2015
- [j15]Johannes Palme, Sepp Hochreiter, Ulrich Bodenhofer:
KeBABS: an R package for kernel-based analysis of biological sequences. Bioinform. 31(15): 2574-2576 (2015) - [j14]Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map. Bioinform. 31(20): 3392-3394 (2015) - [j13]Ulrich Bodenhofer, Enrico Bonatesta, Christoph Horejs-Kainrath, Sepp Hochreiter:
msa: an R package for multiple sequence alignment. Bioinform. 31(24): 3997-3999 (2015) - [c16]Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter:
Rectified Factor Networks. NIPS 2015: 1855-1863 - [i5]Djork-Arné Clevert, Thomas Unterthiner, Andreas Mayr, Hubert Ramsauer, Sepp Hochreiter:
Rectified Factor Networks. CoRR abs/1502.06464 (2015) - [i4]Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter:
Toxicity Prediction using Deep Learning. CoRR abs/1503.01445 (2015) - 2014
- [j12]Marc Streit, Samuel Gratzl, Michael Gillhofer, Andreas Mayr, Andreas Mitterecker, Sepp Hochreiter:
Furby: fuzzy force-directed bicluster visualization. BMC Bioinform. 15(S-6): S4 (2014) - 2013
- [i3]Andreas Bender, Hinrich W. H. Göhlmann, Sepp Hochreiter, Ziv Shkedy:
Computational Methods Aiding Early-Stage Drug Design (Dagstuhl Seminar 13212). Dagstuhl Reports 3(5): 78-94 (2013) - 2011
- [j11]Ulrich Bodenhofer, Andreas Kothmeier, Sepp Hochreiter:
APCluster: an R package for affinity propagation clustering. Bioinform. 27(17): 2463-2464 (2011) - 2010
- [j10]Sepp Hochreiter, Ulrich Bodenhofer, Martin Heusel, Andreas Mayr, Andreas Mitterecker, Adetayo Kasim, Tatsiana Khamiakova, Suzy Van Sanden, Dan Lin, Willem Talloen, Luc Bijnens, Hinrich W. H. Göhlmann, Ziv Shkedy, Djork-Arné Clevert:
FABIA: factor analysis for bicluster acquisition. Bioinform. 26(12): 1520-1527 (2010)
2000 – 2009
- 2009
- [c15]Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ionescu, Sepp Hochreiter:
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations. IFSA/EUSFLAT Conf. 2009: 1376-1381 - [e2]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
Similarity-based learning on structures, 15.02. - 20.02.2009. Dagstuhl Seminar Proceedings 09081, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2009 [contents] - [i2]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Abstracts Collection - Similarity-based learning on structures. Similarity-based learning on structures 2009 - [i1]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Summary - Similarity-based learning on structures. Similarity-based learning on structures 2009 - 2008
- [j9]Tilman Knebel, Sepp Hochreiter, Klaus Obermayer:
An SMO Algorithm for the Potential Support Vector Machine. Neural Comput. 20(1): 271-287 (2008) - 2007
- [j8]Sepp Hochreiter, Martin Heusel, Klaus Obermayer:
Fast model-based protein homology detection without alignment. Bioinform. 23(14): 1728-1736 (2007) - [j7]Willem Talloen, Djork-Arné Clevert, Sepp Hochreiter, Dhammika Amaratunga, Luc Bijnens, Stefan Kass, Hinrich W. H. Göhlmann:
I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data. Bioinform. 23(21): 2897-2902 (2007) - [c14]Steffen Grünewälder, Sepp Hochreiter, Klaus Obermayer:
Optimality of LSTD and its Relation to MC. IJCNN 2007: 338-343 - [p2]Sepp Hochreiter, Michael C. Mozer:
Monaural Speech Separation by Support Vector Machines: Bridging the Divide Between Supervised and Unsupervised Learning Methods. Blind Speech Separation 2007: 411-428 - [e1]Sepp Hochreiter, Roland Wagner:
Bioinformatics Research and Development, First International Conference, BIRD 2007, Berlin, Germany, March 12-14, 2007, Proceedings. Lecture Notes in Computer Science 4414, Springer 2007, ISBN 978-3-540-71232-9 [contents] - 2006
- [j6]Sepp Hochreiter, Djork-Arné Clevert, Klaus Obermayer:
A new summarization method for affymetrix probe level data. Bioinform. 22(8): 943-949 (2006) - [j5]Sepp Hochreiter, Klaus Obermayer:
Support Vector Machines for Dyadic Data. Neural Comput. 18(6): 1472-1510 (2006) - [c13]Johannes Mohr, Imke Puls, Jana Wrase, Sepp Hochreiter, Andreas Heinz, Klaus Obermayer:
P-SVM Variable Selection for Discovering Dependencies Between Genetic and Brain Imaging Data. IJCNN 2006: 5020-5027 - [p1]Sepp Hochreiter, Klaus Obermayer:
Nonlinear Feature Selection with the Potential Support Vector Machine. Feature Extraction 2006: 419-438 - 2005
- [c12]Sepp Hochreiter, Klaus Obermayer:
Optimal gradient-based learning using importance weights. IJCNN 2005: 114-119 - [c11]Sepp Hochreiter, Klaus Obermayer:
Optimal kernels for unsupervised learning. IJCNN 2005: 1895-1899 - 2002
- [c10]Sepp Hochreiter, Michael Mozer, Klaus Obermayer:
Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. NIPS 2002: 545-552 - [c9]Sepp Hochreiter, Klaus Obermayer:
Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers. NIPS 2002: 889-896 - 2001
- [c8]Sepp Hochreiter, A. Steven Younger, Peter R. Conwell:
Learning to Learn Using Gradient Descent. ICANN 2001: 87-94 - [c7]Sepp Hochreiter, Michael Mozer:
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. ICANN 2001: 661-668 - 2000
- [c6]Sepp Hochreiter, Michael Mozer:
Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models. NIPS 2000: 535-541
1990 – 1999
- 1999
- [j4]Sepp Hochreiter, Jürgen Schmidhuber:
Feature Extraction Through LOCOCODE. Neural Comput. 11(3): 679-714 (1999) - [c5]Sepp Hochreiter, Jürgen Schmidhuber:
Nonlinear ICA through low-complexity autoencoders. ISCAS (5) 1999: 53-56 - 1998
- [j3]Sepp Hochreiter:
The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 6(2): 107-116 (1998) - [c4]Sepp Hochreiter, Jürgen Schmidhuber:
Source Separation as a By-Product of Regularization. NIPS 1998: 459-465 - 1997
- [j2]Sepp Hochreiter, Jürgen Schmidhuber:
Flat Minima. Neural Comput. 9(1): 1-42 (1997) - [j1]Sepp Hochreiter, Jürgen Schmidhuber:
Long Short-Term Memory. Neural Comput. 9(8): 1735-1780 (1997) - [c3]Sepp Hochreiter, Jürgen Schmidhuber:
Unsupervised Coding with LOCOCODE. ICANN 1997: 655-660 - 1996
- [c2]Sepp Hochreiter, Jürgen Schmidhuber:
LSTM can Solve Hard Long Time Lag Problems. NIPS 1996: 473-479 - 1994
- [c1]Sepp Hochreiter, Jürgen Schmidhuber:
Simplifying Neural Nets by Discovering Flat Minima. NIPS 1994: 529-536
Coauthor Index
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