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2020 – today
- 2024
[c7]Vivien Cabannes, Berfin Simsek, Alberto Bietti:
Learning Associative Memories with Gradient Descent. ICML 2024- [c6]Flavio Martinelli, Berfin Simsek, Wulfram Gerstner, Johanni Brea:
Expand-and-Cluster: Parameter Recovery of Neural Networks. ICML 2024 - [i12]Zhengqing Wu, Berfin Simsek, François Ged:
The Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escaping, and Network Embedding. CoRR abs/2402.05626 (2024) - [i11]Vivien Cabannes, Berfin Simsek, Alberto Bietti:
Learning Associative Memories with Gradient Descent. CoRR abs/2402.18724 (2024) - [i10]Berfin Simsek, Amire Bendjeddou, Daniel Hsu:
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence. CoRR abs/2411.08798 (2024) - 2023
- [c5]Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea:
Should Under-parameterized Student Networks Copy or Average Teacher Weights? NeurIPS 2023 - [i9]Johanni Brea, Flavio Martinelli
, Berfin Simsek, Wulfram Gerstner:
MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately). CoRR abs/2301.10638 (2023) - [i8]Flavio Martinelli, Berfin Simsek, Johanni Brea, Wulfram Gerstner:
Expand-and-Cluster: Exact Parameter Recovery of Neural Networks. CoRR abs/2304.12794 (2023) - [i7]Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea:
Should Under-parameterized Student Networks Copy or Average Teacher Weights? CoRR abs/2311.01644 (2023) - 2022
- [i6]Berfin Simsek, Melissa Hall, Levent Sagun:
Understanding out-of-distribution accuracies through quantifying difficulty of test samples. CoRR abs/2203.15100 (2022) - 2021
- [c4]Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea:
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. ICML 2021: 9722-9732 - [i5]Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea:
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. CoRR abs/2105.12221 (2021) - [i4]Arthur Jacot, François Ged, Franck Gabriel, Berfin Simsek, Clément Hongler:
Deep Linear Networks Dynamics: Low-Rank Biases Induced by Initialization Scale and L2 Regularization. CoRR abs/2106.15933 (2021) - 2020
- [c3]Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel:
Implicit Regularization of Random Feature Models. ICML 2020: 4631-4640 - [c2]Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel:
Kernel Alignment Risk Estimator: Risk Prediction from Training Data. NeurIPS 2020 - [i3]Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel:
Implicit Regularization of Random Feature Models. CoRR abs/2002.08404 (2020) - [i2]Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel:
Kernel Alignment Risk Estimator: Risk Prediction from Training Data. CoRR abs/2006.09796 (2020)
2010 – 2019
- 2019
- [c1]Berfin Simsek, Alper T. Erdogan:
Online Bounded Component Analysis: A Simple Recurrent Neural Network with Local Update Rule for Unsupervised Separation of Dependent and Independent Sources. ACSSC 2019: 1639-1643 - [i1]Johanni Brea, Berfin Simsek, Bernd Illing, Wulfram Gerstner:
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape. CoRR abs/1907.02911 (2019)
Coauthor Index
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