| Mathematical Capabilities of ChatGPT S Frieder, L Pinchetti, RR Griffiths, T Salvatori, T Lukasiewicz, ... Advances in Neural Information Processing Systems 36, 2024 | 945* | 2024 |
| The Modern Mathematics of Deep Learning J Berner, P Grohs, G Kutyniok, P Petersen Mathematical Aspects of Deep Learning, 1-111, 2022 | 369* | 2022 |
| Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of … J Berner, P Grohs, A Jentzen SIAM Journal on Mathematics of Data Science 2 (3), 631-657, 2020 | 238 | 2020 |
| An optimal control perspective on diffusion-based generative modeling J Berner, L Richter, K Ullrich Transactions on Machine Learning Research, 2024 | 137 | 2024 |
| DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Z Hao, C Su, S Liu, J Berner, C Ying, H Su, A Anandkumar, J Song, J Zhu International Conference on Machine Learning, 2024 | 97 | 2024 |
| Improved sampling via learned diffusions L Richter, J Berner International Conference on Learning Representations, 2024 | 91 | 2024 |
| Group testing for SARS-CoV-2 allows for up to 10-fold efficiency increase across realistic scenarios and testing strategies CM Verdun, T Fuchs, P Harar, D Elbrächter, DS Fischer, J Berner, ... Frontiers in Public Health 9, 583377, 2021 | 85 | 2021 |
| Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning J Berner, M Dablander, P Grohs Advances in Neural Information Processing Systems 33, 2020 | 84 | 2020 |
| Improving diffusion inverse problem solving with decoupled noise annealing B Zhang, W Chu, J Berner, C Meng, A Anandkumar, Y Song Proceedings of the Computer Vision and Pattern Recognition Conference, 20895 …, 2025 | 67 | 2025 |
| Neural Operators with Localized Integral and Differential Kernels M Liu-Schiaffini, J Berner, B Bonev, T Kurth, K Azizzadenesheli, ... International Conference on Machine Learning, 2024 | 62 | 2024 |
| Pretraining codomain attention neural operators for solving multiphysics pdes MA Rahman, RJ George, M Elleithy, D Leibovici, Z Li, B Bonev, C White, ... Advances in Neural Information Processing Systems 37, 104035-104064, 2024 | 47 | 2024 |
| How degenerate is the parametrization of neural networks with the ReLU activation function? J Berner, D Elbrächter, P Grohs Advances in Neural Information Processing Systems, 7790-7801, 2019 | 44* | 2019 |
| Sequential Controlled Langevin Diffusions J Chen, L Richter, J Berner, D Blessing, G Neumann, A Anandkumar The Thirteenth International Conference on Learning Representations, 2025 | 35 | 2025 |
| Underdamped diffusion bridges with applications to sampling D Blessing, J Berner, L Richter, G Neumann The Thirteenth International Conference on Learning Representations, 2025 | 25 | 2025 |
| Dynamical Measure Transport and Neural PDE Solvers for Sampling J Sun, J Berner, L Richter, M Zeinhofer, J Müller, K Azizzadenesheli, ... arXiv preprint arXiv:2407.07873, 2024 | 25* | 2024 |
| Towards a regularity theory for ReLU networks–chain rule and global error estimates J Berner, D Elbrächter, P Grohs, A Jentzen 2019 13th International conference on Sampling Theory and Applications …, 2019 | 24 | 2019 |
| A library for learning neural operators J Kossaifi, N Kovachki, Z Li, D Pitt, M Liu-Schiaffini, V Duruisseaux, ... arXiv preprint arXiv:2412.10354, 2024 | 22 | 2024 |
| Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning L Richter, J Berner International Conference on Machine Learning, 18649-18666, 2022 | 22 | 2022 |
| Large Language Models for Mathematicians S Frieder, J Berner, P Petersen, T Lukasiewicz International Mathematical News 254, 2023 | 19* | 2023 |
| Learning ReLU networks to high uniform accuracy is intractable J Berner, P Grohs, F Voigtlaender International Conference on Learning Representations, 2023 | 19 | 2023 |
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
