Title
Mean-Field Generalisation Bounds for Learning Controls in Stochastic Environments Boris Baros Samuel N. Cohen C. Reisinger AI4CE 102 1 0 21 Aug 2025
Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence Qi Feng Gu Wang 94 1 0 09 Jun 2025
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Haoxuan Chen Yinuo Ren Martin Renqiang Min Lexing Ying Zachary Izzo DiffM MedIm 285 11 0 04 Jun 2025
Non-convex entropic mean-field optimization via Best Response flow Razvan-Andrei Lascu Mateusz B. Majka 170 1 0 28 May 2025
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games Yulong Lu Pierre Monmarché MLT 193 3 0 12 May 2025
Mirror Mean-Field Langevin Dynamics Anming Gu Juno Kim 225 1 0 05 May 2025
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 265 2 0 25 Apr 2025
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble Atsushi Nitanda Anzelle Lee Damian Tan Xing Kai Mizuki Sakaguchi Taiji Suzuki AI4CE 343 2 0 09 Feb 2025
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity Shuailong Zhu Xiaohui Chen 253 1 0 25 Jan 2025
Well-posedness and approximation of reflected McKean-Vlasov SDEs with applications P. D. Hinds A. Sharma M. V. Tretyakov 119 3 0 28 Dec 2024
Linear convergence of proximal descent schemes on the Wasserstein space Razvan-Andrei Lascu Mateusz B. Majka David Siska Łukasz Szpruch 293 1 0 22 Nov 2024
Solving Fredholm Integral Equations of the Second Kind via Wasserstein Gradient Flows F. R. Crucinio A. M. Johansen 123 1 0 29 Sep 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin DynamicsInternational Conference on Learning Representations (ICLR), 2024 Alireza Mousavi-Hosseini Denny Wu Murat A. Erdogdu MLT AI4CE 232 11 0 14 Aug 2024
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior Anming Gu Edward Chien Kristjan Greenewald 298 9 0 11 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Joaquin Fontbona MLT FedML 427 3 0 30 May 2024
Improved Particle Approximation Error for Mean Field Neural Networks Atsushi Nitanda 151 11 0 24 May 2024
Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent Yiwen Kou Zixiang Chen Quanquan Gu Sham Kakade 184 2 0 18 Apr 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes Haoming Yang Ali Hasan Yuting Ng Vahid Tarokh DiffM 169 6 0 15 Apr 2024
Mean-field Analysis on Two-layer Neural Networks from a Kernel PerspectiveInternational Conference on Machine Learning (ICML), 2024 Shokichi Takakura Taiji Suzuki MLT 311 7 0 22 Mar 2024
Mirror Descent-Ascent for mean-field min-max problems Razvan-Andrei Lascu Mateusz B. Majka Lukasz Szpruch 276 1 0 12 Feb 2024
Generalization Error of Graph Neural Networks in the Mean-field RegimeInternational Conference on Machine Learning (ICML), 2024 Gholamali Aminian Yixuan He Gesine Reinert Lukasz Szpruch Samuel N. Cohen 292 4 0 10 Feb 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 404 5 0 26 Dec 2023
Symmetric Mean-field Langevin Dynamics for Distributional Minimax ProblemsInternational Conference on Learning Representations (ICLR), 2023 Juno Kim Kakei Yamamoto Kazusato Oko Zhuoran Yang Taiji Suzuki 294 12 0 02 Dec 2023
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation Nawaf Bou-Rabee Katharina Schuh 128 8 0 22 Aug 2023
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction Taiji Suzuki Denny Wu Atsushi Nitanda 143 20 0 12 Jun 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood EstimationE S A I M: Probability & Statistics (ESAIM-PS), 2023 Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 228 18 0 23 Mar 2023
Doubly Regularized Entropic Wasserstein Barycenters Lénaïc Chizat 240 16 0 21 Mar 2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum ProblemsInternational Conference on Machine Learning (ICML), 2023 Atsushi Nitanda Kazusato Oko Denny Wu Nobuhito Takenouchi Taiji Suzuki 169 4 0 06 Mar 2023
PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium Shihong Ding Hanze Dong Cong Fang Zhouchen Lin Tong Zhang 153 1 0 02 Mar 2023
Mean Field Optimization Problem Regularized by Fisher Information J. Claisse Giovanni Conforti Zhenjie Ren Song-bo Wang 186 5 0 12 Feb 2023
Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field PerspectiveInternational Conference on Machine Learning (ICML), 2022 Yulong Lu MLT AI4CE 204 27 0 17 Dec 2022
Uniform-in-time propagation of chaos for mean field Langevin dynamicsAnnales De L Institut Henri Poincare-probabilites Et Statistiques (Ann. Inst. Henri Poincaré Probab. Stat.), 2022 Fan Chen Zhenjie Ren Song-bo Wang 308 34 0 06 Dec 2022
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 275 5 0 28 Oct 2022
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence Diyuan Wu Vyacheslav Kungurtsev Marco Mondelli 144 3 0 13 Oct 2022
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows F. R. Crucinio Valentin De Bortoli Arnaud Doucet A. M. Johansen 179 3 0 16 Sep 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel MethodsInternational Conference on Learning Representations (ICLR), 2022 Shunta Akiyama Taiji Suzuki 154 8 0 30 May 2022
Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates Jingwei Zhang Xunpeng Huang Jincheng Yu MLT 192 1 0 19 May 2022
Trajectory Inference via Mean-field Langevin in Path SpaceNeural Information Processing Systems (NeurIPS), 2022 Lénaïc Chizat Stephen X. Zhang Matthieu Heitz Geoffrey Schiebinger 320 31 0 14 May 2022
GANs as Gradient Flows that ConvergeJournal of machine learning research (JMLR), 2022 Yu‐Jui Huang Yuchong Zhang 154 6 0 05 May 2022
On Feature Learning in Neural Networks with Global Convergence GuaranteesInternational Conference on Learning Representations (ICLR), 2022 Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 198 15 0 22 Apr 2022
Convex Analysis of the Mean Field Langevin DynamicsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Atsushi Nitanda Denny Wu Taiji Suzuki MLT 353 74 0 25 Jan 2022
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field RegimeInternational Conference on Machine Learning (ICML), 2022 B. Kerimkulov J. Leahy David Siska Lukasz Szpruch 249 21 0 18 Jan 2022
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU NetworksJournal of machine learning research (JMLR), 2021 Aleksandr Shevchenko Vyacheslav Kungurtsev Marco Mondelli MLT 254 15 0 03 Nov 2021
Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation Louis Sharrock N. Kantas P. Parpas G. Pavliotis 183 30 0 25 Jun 2021
Stochastic gradient descent with noise of machine learning type. Part II: Continuous time analysisJournal of nonlinear science (J. Nonlinear Sci.), 2021 Stephan Wojtowytsch 184 37 0 04 Jun 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate AnalysisNeural Information Processing Systems (NeurIPS), 2020 Atsushi Nitanda Denny Wu Taiji Suzuki 347 31 0 31 Dec 2020
Mathematical Models of Overparameterized Neural NetworksProceedings of the IEEE (Proc. IEEE), 2020 Cong Fang Hanze Dong Tong Zhang 253 25 0 27 Dec 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don'tCSIAM Transactions on Applied Mathematics (CSIAM Trans. Appl. Math.), 2020 E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 264 146 0 22 Sep 2020
Ergodicity of the underdamped mean-field Langevin dynamicsThe Annals of Applied Probability (Ann. Appl. Probab.), 2020 A. Kazeykina Zhenjie Ren Xiaolu Tan Junjian Yang 233 18 0 29 Jul 2020
On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures M. Samarin Volker Roth David Belius 100 4 0 24 Jun 2020

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Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks

Annales De L Institut Henri Poincare-probabilites Et Statistiques (Ann. Inst. Henri Poincaré Probab. Stat.), 2019

19 May 2019

Papers citing "Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks"

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Title
Mean-Field Generalisation Bounds for Learning Controls in Stochastic Environments Boris Baros Samuel N. Cohen C. Reisinger AI4CE 102 1 0 21 Aug 2025
Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence Qi Feng Gu Wang 94 1 0 09 Jun 2025
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Haoxuan Chen Yinuo Ren Martin Renqiang Min Lexing Ying Zachary Izzo DiffM MedIm 285 11 0 04 Jun 2025
Non-convex entropic mean-field optimization via Best Response flow Razvan-Andrei Lascu Mateusz B. Majka 170 1 0 28 May 2025
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games Yulong Lu Pierre Monmarché MLT 193 3 0 12 May 2025
Mirror Mean-Field Langevin Dynamics Anming Gu Juno Kim 225 1 0 05 May 2025
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 265 2 0 25 Apr 2025
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble Atsushi Nitanda Anzelle Lee Damian Tan Xing Kai Mizuki Sakaguchi Taiji Suzuki AI4CE 343 2 0 09 Feb 2025
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity Shuailong Zhu Xiaohui Chen 253 1 0 25 Jan 2025
Well-posedness and approximation of reflected McKean-Vlasov SDEs with applications P. D. Hinds A. Sharma M. V. Tretyakov 119 3 0 28 Dec 2024
Linear convergence of proximal descent schemes on the Wasserstein space Razvan-Andrei Lascu Mateusz B. Majka David Siska Łukasz Szpruch 293 1 0 22 Nov 2024
Solving Fredholm Integral Equations of the Second Kind via Wasserstein Gradient Flows F. R. Crucinio A. M. Johansen 123 1 0 29 Sep 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin DynamicsInternational Conference on Learning Representations (ICLR), 2024 Alireza Mousavi-Hosseini Denny Wu Murat A. Erdogdu MLT AI4CE 232 11 0 14 Aug 2024
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior Anming Gu Edward Chien Kristjan Greenewald 298 9 0 11 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Joaquin Fontbona MLT FedML 427 3 0 30 May 2024
Improved Particle Approximation Error for Mean Field Neural Networks Atsushi Nitanda 151 11 0 24 May 2024
Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent Yiwen Kou Zixiang Chen Quanquan Gu Sham Kakade 184 2 0 18 Apr 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes Haoming Yang Ali Hasan Yuting Ng Vahid Tarokh DiffM 169 6 0 15 Apr 2024
Mean-field Analysis on Two-layer Neural Networks from a Kernel PerspectiveInternational Conference on Machine Learning (ICML), 2024 Shokichi Takakura Taiji Suzuki MLT 311 7 0 22 Mar 2024
Mirror Descent-Ascent for mean-field min-max problems Razvan-Andrei Lascu Mateusz B. Majka Lukasz Szpruch 276 1 0 12 Feb 2024
Generalization Error of Graph Neural Networks in the Mean-field RegimeInternational Conference on Machine Learning (ICML), 2024 Gholamali Aminian Yixuan He Gesine Reinert Lukasz Szpruch Samuel N. Cohen 292 4 0 10 Feb 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 404 5 0 26 Dec 2023
Symmetric Mean-field Langevin Dynamics for Distributional Minimax ProblemsInternational Conference on Learning Representations (ICLR), 2023 Juno Kim Kakei Yamamoto Kazusato Oko Zhuoran Yang Taiji Suzuki 294 12 0 02 Dec 2023
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation Nawaf Bou-Rabee Katharina Schuh 128 8 0 22 Aug 2023
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction Taiji Suzuki Denny Wu Atsushi Nitanda 143 20 0 12 Jun 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood EstimationE S A I M: Probability & Statistics (ESAIM-PS), 2023 Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 228 18 0 23 Mar 2023
Doubly Regularized Entropic Wasserstein Barycenters Lénaïc Chizat 240 16 0 21 Mar 2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum ProblemsInternational Conference on Machine Learning (ICML), 2023 Atsushi Nitanda Kazusato Oko Denny Wu Nobuhito Takenouchi Taiji Suzuki 169 4 0 06 Mar 2023
PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium Shihong Ding Hanze Dong Cong Fang Zhouchen Lin Tong Zhang 153 1 0 02 Mar 2023
Mean Field Optimization Problem Regularized by Fisher Information J. Claisse Giovanni Conforti Zhenjie Ren Song-bo Wang 186 5 0 12 Feb 2023
Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field PerspectiveInternational Conference on Machine Learning (ICML), 2022 Yulong Lu MLT AI4CE 204 27 0 17 Dec 2022
Uniform-in-time propagation of chaos for mean field Langevin dynamicsAnnales De L Institut Henri Poincare-probabilites Et Statistiques (Ann. Inst. Henri Poincaré Probab. Stat.), 2022 Fan Chen Zhenjie Ren Song-bo Wang 308 34 0 06 Dec 2022
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 275 5 0 28 Oct 2022
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence Diyuan Wu Vyacheslav Kungurtsev Marco Mondelli 144 3 0 13 Oct 2022
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows F. R. Crucinio Valentin De Bortoli Arnaud Doucet A. M. Johansen 179 3 0 16 Sep 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel MethodsInternational Conference on Learning Representations (ICLR), 2022 Shunta Akiyama Taiji Suzuki 154 8 0 30 May 2022
Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates Jingwei Zhang Xunpeng Huang Jincheng Yu MLT 192 1 0 19 May 2022
Trajectory Inference via Mean-field Langevin in Path SpaceNeural Information Processing Systems (NeurIPS), 2022 Lénaïc Chizat Stephen X. Zhang Matthieu Heitz Geoffrey Schiebinger 320 31 0 14 May 2022
GANs as Gradient Flows that ConvergeJournal of machine learning research (JMLR), 2022 Yu‐Jui Huang Yuchong Zhang 154 6 0 05 May 2022
On Feature Learning in Neural Networks with Global Convergence GuaranteesInternational Conference on Learning Representations (ICLR), 2022 Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 198 15 0 22 Apr 2022
Convex Analysis of the Mean Field Langevin DynamicsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Atsushi Nitanda Denny Wu Taiji Suzuki MLT 353 74 0 25 Jan 2022
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field RegimeInternational Conference on Machine Learning (ICML), 2022 B. Kerimkulov J. Leahy David Siska Lukasz Szpruch 249 21 0 18 Jan 2022
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU NetworksJournal of machine learning research (JMLR), 2021 Aleksandr Shevchenko Vyacheslav Kungurtsev Marco Mondelli MLT 254 15 0 03 Nov 2021
Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation Louis Sharrock N. Kantas P. Parpas G. Pavliotis 183 30 0 25 Jun 2021
Stochastic gradient descent with noise of machine learning type. Part II: Continuous time analysisJournal of nonlinear science (J. Nonlinear Sci.), 2021 Stephan Wojtowytsch 184 37 0 04 Jun 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate AnalysisNeural Information Processing Systems (NeurIPS), 2020 Atsushi Nitanda Denny Wu Taiji Suzuki 347 31 0 31 Dec 2020
Mathematical Models of Overparameterized Neural NetworksProceedings of the IEEE (Proc. IEEE), 2020 Cong Fang Hanze Dong Tong Zhang 253 25 0 27 Dec 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don'tCSIAM Transactions on Applied Mathematics (CSIAM Trans. Appl. Math.), 2020 E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 264 146 0 22 Sep 2020
Ergodicity of the underdamped mean-field Langevin dynamicsThe Annals of Applied Probability (Ann. Appl. Probab.), 2020 A. Kazeykina Zhenjie Ren Xiaolu Tan Junjian Yang 233 18 0 29 Jul 2020
On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures M. Samarin Volker Roth David Belius 100 4 0 24 Jun 2020

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