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Symmetries in Overparametrized Neural Networks: A Mean-Field View

30 May 2024

Papers citing "Symmetries in Overparametrized Neural Networks: A Mean-Field View"

34 / 34 papers shown

Title
Data Augmentation and Regularization for Learning Group Equivariance Oskar Nordenfors Axel Flinth 127 0 0 10 Feb 2025
Approximately Equivariant Graph Networks Ningyuan Huang Ron Levie Soledad Villar 99 19 0 21 Aug 2023
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction Taiji Suzuki Denny Wu Atsushi Nitanda 61 17 0 12 Jun 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance Mircea Petrache Shubhendu Trivedi 75 25 0 27 May 2023
Optimization Dynamics of Equivariant and Augmented Neural Networks Axel Flinth F. Ohlsson 96 7 0 23 Mar 2023
On the symmetries in the dynamics of wide two-layer neural networks Karl Hajjar Lénaïc Chizat 49 11 0 16 Nov 2022
Convex Analysis of the Mean Field Langevin Dynamics Atsushi Nitanda Denny Wu Taiji Suzuki MLT 128 66 0 25 Jan 2022
Homogeneous vector bundles and $G$ -equivariant convolutional neural networks J. Aronsson 69 24 0 12 May 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 362 1,163 0 27 Apr 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 162 198 0 19 Apr 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 102 91 0 25 Feb 2021
Provably Strict Generalisation Benefit for Equivariant Models Bryn Elesedy Sheheryar Zaidi AI4CE 62 88 0 20 Feb 2021
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels Leon Lang Maurice Weiler 87 56 0 21 Oct 2020
A Dynamical Central Limit Theorem for Shallow Neural Networks Zhengdao Chen Grant M. Rotskoff Joan Bruna Eric Vanden-Eijnden 73 30 0 21 Aug 2020
Quantitative Propagation of Chaos for SGD in Wide Neural Networks Valentin De Bortoli Alain Durmus Xavier Fontaine Umut Simsekli 76 25 0 13 Jul 2020
On the Benefits of Invariance in Neural Networks Clare Lyle Mark van der Wilk Marta Z. Kwiatkowska Y. Gal Benjamin Bloem-Reddy OOD BDL 76 96 0 01 May 2020
Convex Optimization on Functionals of Probability Densities T. Nishiyama 33 6 0 16 Feb 2020
Universal Equivariant Multilayer Perceptrons Siamak Ravanbakhsh 150 51 0 07 Feb 2020
General $E(2)$ -Equivariant Steerable CNNs Maurice Weiler Gabriele Cesa 115 525 0 19 Nov 2019
Enhanced Convolutional Neural Tangent Kernels Zhiyuan Li Ruosong Wang Dingli Yu S. Du Wei Hu Ruslan Salakhutdinov Sanjeev Arora 68 133 0 03 Nov 2019
Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks Kaitong Hu Zhenjie Ren David Siska Lukasz Szpruch MLT 65 108 0 19 May 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit Song Mei Theodor Misiakiewicz Andrea Montanari MLT 84 279 0 16 Feb 2019
On the Universality of Invariant Networks Haggai Maron Ethan Fetaya Nimrod Segol Y. Lipman OOD 158 240 0 27 Jan 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 224 316 0 05 Nov 2018
Mean Field Analysis of Neural Networks: A Central Limit Theorem Justin A. Sirignano K. Spiliopoulos MLT 87 194 0 28 Aug 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 221 737 0 24 May 2018
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach Grant M. Rotskoff Eric Vanden-Eijnden 134 123 0 02 May 2018
Universal approximations of invariant maps by neural networks Dmitry Yarotsky 124 213 0 26 Apr 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 105 862 0 18 Apr 2018
A Kernel Theory of Modern Data Augmentation Tri Dao Albert Gu Alexander J. Ratner Virginia Smith Christopher De Sa Christopher Ré 110 193 0 16 Mar 2018
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups Risi Kondor Shubhendu Trivedi MLT 116 500 0 11 Feb 2018
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 427 2,480 0 10 Mar 2017
Equivariance Through Parameter-Sharing Siamak Ravanbakhsh J. Schneider Barnabás Póczós 92 258 0 27 Feb 2017
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 252 3,226 0 15 Jun 2016