| 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 | 1841 | 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 | 334 | 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, 2024 | 176 | 2024 |
| 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 | 31* | 2022 |
| 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 | 17 | 2018 |
| 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 | 15 | 2021 |
| Out-of-class novelty generation: an experimental foundation M Cherti, B Kégl, A Kazakçı 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 15 | 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, ... | 12 | 2018 |
| Digits that are not: Generating new types through deep neural nets A Kazakçı, C Mehdi, B Kégl arXiv preprint arXiv:1606.04345, 2016 | 12 | 2016 |
| De novo drug design with deep generative models: an empirical study M Cherti, B Kégl, A Kazakçı ICLR workshop, 2017 | 9 | 2017 |
| 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 | 4 | 2018 |
| 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 | 3 | 2017 |
| Effect of pre-training scale on intra-and inter-domain transfer for natural and X-Ray chest images M Cherti, J Jitsev MedNeurIPS 2021 workshop, 2021 | 1 | 2021 |
| InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification L Boussioux, T Giro-Larraz, C Guille-Escuret, M Cherti, B Kégl arXiv preprint arXiv:1906.11898, 2019 | 1 | 2019 |
| 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 | | 2024 |
| 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 | | 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 | | 2024 |
| A Comparative Study on Generative Models for High Resolution Solar Observation Imaging M Cherti, A Czernik, S Kesselheim, F Effenberger, J Jitsev arXiv preprint arXiv:2304.07169, 2023 | | 2023 |
| 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 | | 2023 |
Balazs KEGLResearch scientist, Paris AI leader, Noah's Ark Lab, Huawei Research在 huawei.com 的电子邮件经过验证
Balazs KEGLResearch scientist, Paris AI leader, Noah's Ark Lab, Huawei Research在 huawei.com 的电子邮件经过验证
Akin KazakciAssociate Professor, Mines Paristech在 mines-paristech.fr 的电子邮件经过验证