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ORCIDJenia Jitsev
Person information
- affiliation: LAION, Hamburg, Germany
- affiliation: Jülich Supercomputing Center (JSC), Germany
- affiliation: Research Center Jülich (FZJ), Germany
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2020 – today
- 2024
[i14]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024)- 2023
- [c19]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible Scaling Laws for Contrastive Language-Image Learning. CVPR 2023: 2818-2829 - [c18]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [i13]Mehdi Cherti, Alexander Czernik, Stefan Kesselheim, Frederic Effenberger, Jenia Jitsev:
A Comparative Study on Generative Models for High Resolution Solar Observation Imaging. CoRR abs/2304.07169 (2023) - [i12]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i11]Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, Ludwig Schmidt:
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. CoRR abs/2308.01390 (2023) - 2022
- [c17]Mehdi Cherti, Jenia Jitsev:
Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images. IJCNN 2022: 1-9 - [c16]Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev:
LAION-5B: An open large-scale dataset for training next generation image-text models. NeurIPS 2022 - [i10]Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev:
LAION-5B: An open large-scale dataset for training next generation image-text models. CoRR abs/2210.08402 (2022) - [i9]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning. CoRR abs/2210.16110 (2022) - [i8]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible scaling laws for contrastive language-image learning. CoRR abs/2212.07143 (2022) - 2021
- [c15]Stefan Kesselheim, Andreas Herten
, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona, Alexander Schug, Alexandre Strube, Roshni Kamath, Martin G. Schultz, Morris Riedel, Thomas Lippert:
JUWELS Booster - A Supercomputer for Large-Scale AI Research. ISC Workshops 2021: 453-468 - [i7]Marcel Aach, Jens Henrik Göbbert, Jenia Jitsev:
Generalization over different cellular automata rules learned by a deep feed-forward neural network. CoRR abs/2103.14886 (2021) - [i6]Mehdi Cherti, Jenia Jitsev:
Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images. CoRR abs/2106.00116 (2021) - [i5]Stefan Kesselheim, Andreas Herten, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona, Alexander Schug, Alexandre Strube, Roshni Kamath, Martin G. Schultz, Morris Riedel, Thomas Lippert:
JUWELS Booster - A Supercomputer for Large-Scale AI Research. CoRR abs/2108.11976 (2021) - [i4]Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, Aran Komatsuzaki:
LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs. CoRR abs/2111.02114 (2021) - 2020
- [c14]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoG 2020: 447-454 - [c13]Run Zhang, Gabriele Cavallaro, Jenia Jitsev:
Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning. IGARSS 2020: 617-620 - [c12]Rocco Sedona, Gabriele Cavallaro, Jenia Jitsev, Alexandre Strube, Morris Riedel, Matthias Book:
Scaling Up a Multispectral Resnet-50 to 128 GPUs. IGARSS 2020: 1058-1061 - [c11]Mario Rüttgers, Seong-Ryong Koh, Jenia Jitsev, Wolfgang Schröder, Andreas Lintermann:
Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning. ISC Workshops 2020: 81-101 - [i3]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoRR abs/2004.00567 (2020)
2010 – 2019
- 2019
- [j3]Rocco Sedona, Gabriele Cavallaro, Jenia Jitsev, Alexandre Strube, Morris Riedel, Jón Atli Benediktsson:
Remote Sensing Big Data Classification with High Performance Distributed Deep Learning. Remote. Sens. 11(24): 3056 (2019) - [i2]Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, Jenia Jitsev, Heinz Pitsch:
Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows. CoRR abs/1911.11380 (2019) - 2018
- [c10]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards Prediction of Turbulent Flows at High Reynolds Numbers Using High Performance Computing Data and Deep Learning. ISC Workshops 2018: 614-623 - 2014
- [c9]Jenia Jitsev:
Self-generated Off-line Memory Reprocessing Strongly Improves Generalization in a Hierarchical Recurrent Neural Network. ICANN 2014: 659-666 - 2012
- [c8]Jenia Jitsev, Nobi Abraham, Abigail Morrison, Marc Tittgemeyer:
Learning from Delayed Reward und Punishment in a Spiking Neural Network Model of Basal Ganglia with Opposing D1/D2 Plasticity. ICANN (1) 2012: 459-466 - [c7]Jenia Jitsev, Abigail Morrison, Marc Tittgemeyer:
Learning from positive and negative rewards in a spiking neural network model of basal ganglia. IJCNN 2012: 1-8 - 2011
- [j2]Nico S. Gorbach, Christoph Schütte, Corina Melzer, Mathias Goldau, Olivia Sujazow, Jenia Jitsev, Tania S. Douglas, Marc Tittgemeyer:
Hierarchical Information-Based Clustering for Connectivity-Based Cortex Parcellation. Frontiers Neuroinformatics 5: 18 (2011) - [c6]Yasuomi D. Sato, Jenia Jitsev, Jörg Bornschein, Daniela Pamplona, Christian Keck, Christoph von der Malsburg:
A Gabor Wavelet Pyramid-Based Object Detection Algorithm. ISNN (2) 2011: 232-240 - [c5]Nico S. Gorbach, Silvan Siep, Jenia Jitsev, Corina Melzer, Marc Tittgemeyer:
Information-Theoretic Connectivity-Based Cortex Parcellation. MLINI 2011: 186-193 - 2010
- [c4]Yasuomi D. Sato, Jenia Jitsev, Christoph von der Malsburg:
Visual Object Detection by Specifying the Scale and Rotation Transformations. ICONIP (2) 2010: 616-624 - [c3]Jenia Jitsev, Christoph von der Malsburg:
Off-line memory reprocessing following on-line unsupervised learning strongly improves recognition performance in a hierarchical visual memory. IJCNN 2010: 1-8 - [c2]Yasuomi D. Sato, Jenia Jitsev, Thomas Burwick, Christoph von der Malsburg:
Dynamic link models for global decision making with binding-by-synchrony. NaBIC 2010: 201-208
2000 – 2009
- 2009
- [j1]Jenia Jitsev, Christoph von der Malsburg:
Experience-driven formation of parts-based representations in a model of layered visual memory. Frontiers Comput. Neurosci. 3: 15 (2009) - [i1]Jenia Jitsev, Christoph von der Malsburg:
Experience-driven formation of parts-based representations in a model of layered visual memory. CoRR abs/0905.2125 (2009) - 2008
- [c1]Yasuomi D. Sato, Jenia Jitsev, Christoph von der Malsburg:
A Visual Object Recognition System Invariant to Scale and Rotation. ICANN (1) 2008: 991-1000
Coauthor Index
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last updated on 2024-05-22 23:04 CEST by the dblp team
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