| Laion-5b: An open large-scale dataset for training next generation image-text models C Schuhmann, R Beaumont, R Vencu, C Gordon, R Wightman, M Cherti, ... Advances in neural information processing systems 35, 25278-25294, 2022 | 3285 | 2022 |
| Reproducible scaling laws for contrastive language-image learning M Cherti, R Beaumont, R Wightman, M Wortsman, G Ilharco, C Gordon, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 784 | 2023 |
| Datacomp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... Advances in Neural Information Processing Systems 36, 27092-27112, 2023 | 396 | 2023 |
| Alice in wonderland: Simple tasks showing complete reasoning breakdown in state-of-the-art large language models M Nezhurina, L Cipolina-Kun, M Cherti, J Jitsev arXiv preprint arXiv:2406.02061, 2024 | 49 | 2024 |
| Laion-5b: An open large-scale dataset for training next generation image-text models, 2022 C Schuhmann, R Beaumont, R Vencu, C Gordon, R Wightman, M Cherti, ... URL https://arxiv. org/abs/2210.08402, 2022 | 45 | 2022 |
| Effect of pre-training scale on intra-and inter-domain, full and few-shot transfer learning for natural and X-ray chest images M Cherti, J Jitsev 2022 International Joint Conference on Neural Networks (IJCNN), 1-9, 2022 | 39* | 2022 |
| Juwels booster–a supercomputer for large-scale ai research S Kesselheim, A Herten, K Krajsek, J Ebert, J Jitsev, M Cherti, M Langguth, ... High Performance Computing: ISC High Performance Digital 2021 International …, 2021 | 25 | 2021 |
| Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach LMM Le, B Kégl, A Gramfort, C Marini, D Nguyen, M Cherti, S Tfaili, ... Talanta 184, 260-265, 2018 | 20 | 2018 |
| Out-of-class novelty generation: an experimental foundation M Cherti, B Kégl, A Kazakçı 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 16 | 2017 |
| The RAMP framework: from reproducibility to transparency in the design and optimization of scientific workflows B Kégl, A Boucaud, M Cherti, A Kazakci, A Gramfort, G Lemaitre, ... | 14 | 2018 |
| Digits that are not: Generating new types through deep neural nets A Kazakçı, C Mehdi, B Kégl arXiv preprint arXiv:1606.04345, 2016 | 13 | 2016 |
| De novo drug design with deep generative models: an empirical study M Cherti, B Kégl, A Kazakçı ICLR workshop, 2017 | 10 | 2017 |
| A Practitioner's Guide to Continual Multimodal Pretraining K Roth, V Udandarao, S Dziadzio, A Prabhu, M Cherti, O Vinyals, ... arXiv preprint arXiv:2408.14471, 2024 | 7 | 2024 |
| Application-driven exascale: The JUPITER benchmark suite A Herten, S Achilles, D Alvarez, J Badwaik, E Behle, M Bode, T Breuer, ... SC24: International Conference for High Performance Computing, Networking …, 2024 | 6 | 2024 |
| Spurious samples in deep generative models: Bug or feature? B Kégl, M Cherti, A Kazakçı arXiv preprint arXiv:1810.01876, 2018 | 5 | 2018 |
| Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments M Cherti Université Paris-Saclay, 2018 | 5 | 2018 |
| Flux density distribution forecasting in concentrated solar tower plants: A data-driven approach M Kuhl, M Pargmann, M Cherti, J Jitsev, DM Quinto, R Pitz-Paal Solar Energy 282, 112894, 2024 | 4 | 2024 |
| In-situ UNet-based heliostat beam characterization method for precise flux calculation using the camera-target method M Kuhl, M Pargmann, M Cherti, J Jitsev, DM Quinto, R Pitz-Paal Solar Energy 279, 112811, 2024 | 2 | 2024 |
| Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy L Le, C Marini, A Gramfort, D Nguyen, M Cherti, S Tfaili, A Tfayli, ... arXiv preprint arXiv:1705.07099, 2017 | 2 | 2017 |
| Datacomp: In search of the next generation of multimodal datasets S Yitzhak Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, ... arXiv e-prints, arXiv: 2304.14108, 2023 | 1 | 2023 |
Balazs KEGLResearch scientist, Paris AI leader, Noah's Ark Lab, Huawei ResearchAdresse e-mail validée de huawei.com
