Mean Field Analysis of Neural Networks: A Central Limit Theorem

28 August 2018

Papers citing "Mean Field Analysis of Neural Networks: A Central Limit Theorem"

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Title
Mirror Mean-Field Langevin Dynamics Anming Gu Juno Kim 31 0 0 05 May 2025
Don't be lazy: CompleteP enables compute-efficient deep transformers Nolan Dey Bin Claire Zhang Lorenzo Noci Mufan Li Blake Bordelon Shane Bergsma Cengiz Pehlevan Boris Hanin Joel Hestness 44 0 0 02 May 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 61 1 0 10 Jan 2025
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 63 0 0 08 Oct 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 50 2 0 30 May 2024
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions Luca Arnaboldi Yatin Dandi Florent Krzakala Luca Pesce Ludovic Stephan 70 12 0 24 May 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 40 4 0 26 Dec 2023
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks Behrad Moniri Donghwan Lee Hamed Hassani Yan Sun MLT 40 19 0 11 Oct 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 31 11 0 12 Jul 2023
Understanding the Initial Condensation of Convolutional Neural Networks Zhangchen Zhou Hanxu Zhou Yuqing Li Zhi-Qin John Xu MLT AI4CE 26 5 0 17 May 2023
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance Krishnakumar Balasubramanian Promit Ghosal Ye He 38 5 0 03 Apr 2023
Phase Diagram of Initial Condensation for Two-layer Neural Networks Zheng Chen Yuqing Li Tao Luo Zhaoguang Zhou Z. Xu MLT AI4CE 49 8 0 12 Mar 2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems Atsushi Nitanda Kazusato Oko Denny Wu Nobuhito Takenouchi Taiji Suzuki 32 3 0 06 Mar 2023
Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent Benjamin Gess Sebastian Kassing Vitalii Konarovskyi DiffM 32 6 0 14 Feb 2023
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks Luca Arnaboldi Ludovic Stephan Florent Krzakala Bruno Loureiro MLT 38 31 0 12 Feb 2023
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models Yufeng Zhang Boyi Liu Qi Cai Lingxiao Wang Zhaoran Wang 53 11 0 30 Dec 2022
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 25 5 0 28 Oct 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 43 1 0 25 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 26 5 0 20 Oct 2022
Neural parameter calibration for large-scale multi-agent models Thomas Gaskin G. Pavliotis Mark Girolami AI4TS 26 23 0 27 Sep 2022
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks Andrew M. Saxe Shagun Sodhani Sam Lewallen AI4CE 30 34 0 21 Jul 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 22 114 0 30 Jun 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 62 58 0 08 Jun 2022
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width Hanxu Zhou Qixuan Zhou Zhenyuan Jin Tao Luo Yaoyu Zhang Zhi-Qin John Xu 25 20 0 24 May 2022
Mean-Field Nonparametric Estimation of Interacting Particle Systems Rentian Yao Xiaohui Chen Yun Yang 43 9 0 16 May 2022
Provably convergent quasistatic dynamics for mean-field two-player zero-sum games Chao Ma Lexing Ying MLT 34 11 0 15 Feb 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks R. Veiga Ludovic Stephan Bruno Loureiro Florent Krzakala Lenka Zdeborová MLT 10 31 0 01 Feb 2022
Convex Analysis of the Mean Field Langevin Dynamics Atsushi Nitanda Denny Wu Taiji Suzuki MLT 68 64 0 25 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 33 66 0 19 Jan 2022
Asymptotic properties of one-layer artificial neural networks with sparse connectivity Christian Hirsch Matthias Neumann Volker Schmidt 21 1 0 01 Dec 2021
Parallel Deep Neural Networks Have Zero Duality Gap Yifei Wang Tolga Ergen Mert Pilanci 79 10 0 13 Oct 2021
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Marylou Gabrié Joan Bruna Eric Vanden-Eijnden FedML 35 6 0 11 Jul 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 42 75 0 28 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel A. Gretton 52 37 0 16 Jun 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Eric Vanden-Eijnden Joan Bruna BDL 33 9 0 15 Apr 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network Mo Zhou Rong Ge Chi Jin 74 44 0 04 Feb 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 130 165 0 29 Jan 2021
Align, then memorise: the dynamics of learning with feedback alignment Maria Refinetti Stéphane dÁscoli Ruben Ohana Sebastian Goldt 26 36 0 24 Nov 2020
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 32 61 0 23 Sep 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 22 133 0 22 Sep 2020
Quantitative Propagation of Chaos for SGD in Wide Neural Networks Valentin De Bortoli Alain Durmus Xavier Fontaine Umut Simsekli 30 25 0 13 Jul 2020
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 41 100 0 25 Jun 2020
What Do Neural Networks Learn When Trained With Random Labels? Hartmut Maennel Ibrahim M. Alabdulmohsin Ilya O. Tolstikhin R. Baldock Olivier Bousquet Sylvain Gelly Daniel Keysers FedML 45 87 0 18 Jun 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 39 78 0 11 Mar 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat Francis R. Bach MLT 36 327 0 11 Feb 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 36 6 0 07 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 27 102 0 30 Dec 2019
The Local Elasticity of Neural Networks Hangfeng He Weijie J. Su 40 44 0 15 Oct 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 54 626 0 14 Aug 2019
Sparse Optimization on Measures with Over-parameterized Gradient Descent Lénaïc Chizat 21 92 0 24 Jul 2019