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Mehdi Cherti
Mehdi Cherti
Verified email at fz-juelich.de - Homepage
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Cited by
Year
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
22852022
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
4932023
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
2332024
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
362022
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
33*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
182018
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
172021
Out-of-class novelty generation: an experimental foundation
M Cherti, B Kégl, A Kazakçı
2017 IEEE 29th International Conference on Tools with Artificial …, 2017
162017
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, ...
132018
Digits that are not: Generating new types through deep neural nets
A Kazakçı, C Mehdi, B Kégl
arXiv preprint arXiv:1606.04345, 2016
132016
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
122024
De novo drug design with deep generative models: an empirical study
M Cherti, B Kégl, A Kazakçı
ICLR workshop, 2017
92017
Spurious samples in deep generative models: Bug or feature?
B Kégl, M Cherti, A Kazakçı
arXiv preprint arXiv:1810.01876, 2018
52018
Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments
M Cherti
Université Paris-Saclay, 2018
42018
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
32017
Application-driven exascale: The JUPITER benchmark suite
A Herten, S Achilles, D Alvarez, J Badwaik, E Behle, M Bode, T Breuer, ...
arXiv preprint arXiv:2408.17211, 2024
22024
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
22021
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
12024
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
12019
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
2024
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