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"

47 / 47 papers shown

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 Bill Li Blake Bordelon Shane Bergsma C. Pehlevan Boris Hanin Joel Hestness 39 0 0 02 May 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 59 1 0 10 Jan 2025
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 61 0 0 08 Oct 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 38 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 61 12 0 24 May 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 34 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 Edgar Dobriban MLT 34 19 0 11 Oct 2023
Quantitative CLTs in Deep Neural Networks Stefano Favaro Boris Hanin Domenico Marinucci I. Nourdin G. Peccati BDL 23 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 23 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 28 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 43 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 24 3 0 06 Mar 2023
Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent Benjamin Gess Sebastian Kassing Vitalii Konarovskyi DiffM 26 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 30 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 45 11 0 30 Dec 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 40 1 0 25 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 20 5 0 20 Oct 2022
Neural parameter calibration for large-scale multi-agent models Thomas Gaskin G. Pavliotis Mark Girolami AI4TS 23 23 0 27 Sep 2022
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks Andrew M. Saxe Shagun Sodhani Sam Lewallen AI4CE 28 34 0 21 Jul 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 17 112 0 30 Jun 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 49 59 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 22 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 24 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 59 64 0 25 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 25 65 0 19 Jan 2022
Asymptotic properties of one-layer artificial neural networks with sparse connectivity Christian Hirsch Matthias Neumann Volker Schmidt 11 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 32 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 31 74 0 28 Jun 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 122 165 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 21 61 0 23 Sep 2020
Quantitative Propagation of Chaos for SGD in Wide Neural Networks Valentin De Bortoli Alain Durmus Xavier Fontaine Umut Simsekli 16 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 33 100 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 40 86 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 31 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 16 327 0 11 Feb 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 28 6 0 07 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 21 102 0 30 Dec 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 39 624 0 14 Aug 2019
Theory of the Frequency Principle for General Deep Neural Networks Tao Luo Zheng Ma Zhi-Qin John Xu Yaoyu Zhang 18 78 0 21 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim A. Gretton 24 158 0 11 Jun 2019
Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections E. Weinan Chao Ma Qingcan Wang Lei Wu MLT 24 22 0 10 Apr 2019
Unbiased deep solvers for linear parametric PDEs Marc Sabate Vidales David Siska Lukasz Szpruch OOD 24 7 0 11 Oct 2018