Implicit regularization of random feature models A Jacot, B Simsek, F Spadaro, C Hongler, F Gabriel International Conference on Machine Learning, 4631-4640, 2020 | 96 | 2020 |
Geometry of the loss landscape in overparameterized neural networks: Symmetries and invariances B Simsek, F Ged, A Jacot, F Spadaro, C Hongler, W Gerstner, J Brea International Conference on Machine Learning, 9722-9732, 2021 | 77 | 2021 |
Kernel alignment risk estimator: Risk prediction from training data A Jacot, B Simsek, F Spadaro, C Hongler, F Gabriel Advances in neural information processing systems 33, 15568-15578, 2020 | 58 | 2020 |
Saddle-to-saddle dynamics in deep linear networks: Small initialization training, symmetry, and sparsity A Jacot, F Ged, B Şimşek, C Hongler, F Gabriel arXiv preprint arXiv:2106.15933, 2021 | 57* | 2021 |
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape J Brea, B Simsek, B Illing, W Gerstner arXiv preprint arXiv:1907.02911, 2019 | 50 | 2019 |
Understanding out-of-distribution accuracies through quantifying difficulty of test samples B Simsek, M Hall, L Sagun arXiv preprint arXiv:2203.15100, 2022 | 6 | 2022 |
Learning associative memories with gradient descent V Cabannes, B Simsek, A Bietti arXiv preprint arXiv:2402.18724, 2024 | 4 | 2024 |
Expand-and-cluster: Exact parameter recovery of neural networks F Martinelli, B Simsek, J Brea, W Gerstner arXiv preprint arXiv:2304.12794, 2023 | 4 | 2023 |
Mlpgradientflow: going with the flow of multilayer perceptrons (and finding minima fast and accurately) J Brea, F Martinelli, B Şimşek, W Gerstner arXiv preprint arXiv:2301.10638, 2023 | 3 | 2023 |
Online bounded component analysis: A simple recurrent neural network with local update rule for unsupervised separation of dependent and independent sources B Simsek, AT Erdogan 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1639-1643, 2019 | 3 | 2019 |
Should Under-parameterized Student Networks Copy or Average Teacher Weights? B Simsek, A Bendjeddou, W Gerstner, J Brea Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
The Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escaping, and Network Embedding Z Wu, B Simsek, F Ged arXiv preprint arXiv:2402.05626, 2024 | | 2024 |
Statistical physics, Bayesian inference and neural information processing E Grant, S Nestler, B Şimşek, S Solla arXiv preprint arXiv:2309.17006, 2023 | | 2023 |
Expand-and-Cluster: Parameter Recovery of Neural Networks F Martinelli, B Simsek, W Gerstner, J Brea arXiv preprint arXiv:2304.12794, 2023 | | 2023 |
A Theory of Finite-Width Neural Networks: Generalization, Scaling Laws, and the Loss Landscape B Simsek EPFL, 2023 | | 2023 |
CSFT JR Fageot, LS Field, FR Gabriel, FG Ged, E Golikov, LPA Hardiman, ... | | |