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Machine Learning from a Continuous Viewpoint

30 December 2019

E. Weinan

Chao Ma

Lei Wu

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Papers citing "Machine Learning from a Continuous Viewpoint"

40 / 40 papers shown

Title
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 91 2 0 21 Nov 2021
Large-time asymptotics in deep learning Carlos Esteve Borjan Geshkovski Dario Pighin Enrique Zuazua 342 34 0 06 Aug 2020
Mean-Field Neural ODEs via Relaxed Optimal Control Jean-François Jabir D. vSivska Lukasz Szpruch MLT 96 38 0 11 Dec 2019
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks David Pfau J. Spencer A. G. Matthews W. Foulkes 84 465 0 05 Sep 2019
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 122 32 0 28 Jun 2019
The Barron Space and the Flow-induced Function Spaces for Neural Network Models E. Weinan Chao Ma Lei Wu 71 110 0 18 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 116 164 0 11 Jun 2019
A mean-field limit for certain deep neural networks Dyego Araújo R. Oliveira Daniel Yukimura AI4CE 66 70 0 01 Jun 2019
A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics E. Weinan Chao Ma Lei Wu MLT 64 123 0 08 Apr 2019
Mean Field Analysis of Deep Neural Networks Justin A. Sirignano K. Spiliopoulos 84 82 0 11 Mar 2019
A Priori Estimates of the Population Risk for Residual Networks E. Weinan Chao Ma Qingcan Wang UQCV 74 61 0 06 Mar 2019
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks Phan-Minh Nguyen AI4CE 60 72 0 07 Feb 2019
Global convergence of neuron birth-death dynamics Grant M. Rotskoff Samy Jelassi Joan Bruna Eric Vanden-Eijnden 49 46 0 05 Feb 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 124 520 0 19 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 244 1,659 0 28 Dec 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,229 0 11 Oct 2018
Mean Field Analysis of Neural Networks: A Central Limit Theorem Justin A. Sirignano K. Spiliopoulos MLT 77 194 0 28 Aug 2018
Learning with SGD and Random Features Luigi Carratino Alessandro Rudi Lorenzo Rosasco 53 78 0 17 Jul 2018
A Mean-Field Optimal Control Formulation of Deep Learning Weinan E Jiequn Han Qianxiao Li OOD 108 187 0 03 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 443 5,168 0 19 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 214 737 0 24 May 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
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 93 32 0 13 Apr 2018
Solving for high dimensional committor functions using artificial neural networks Y. Khoo Jianfeng Lu Lexing Ying 67 137 0 28 Feb 2018
Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients? Boris Hanin 72 254 0 11 Jan 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 210 505 0 27 Oct 2017
Maximum Principle Based Algorithms for Deep Learning Qianxiao Li Long Chen Cheng Tai E. Weinan 103 224 0 26 Oct 2017
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 123 1,390 0 30 Sep 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 93 2,067 0 24 Aug 2017
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations Weinan E Jiequn Han Arnulf Jentzen 125 797 0 15 Jun 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 152 733 0 09 May 2017
Deep Learning Approximation for Stochastic Control Problems Jiequn Han E. Weinan BDL 61 197 0 02 Nov 2016
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 174 5,042 0 27 Jun 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,196 0 16 Mar 2016
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut Nicolas Flammarion Francis R. Bach ODL 59 227 0 17 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Neural Network with Unbounded Activation Functions is Universal Approximator Sho Sonoda Noboru Murata 70 336 0 14 May 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 184 706 0 30 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013
Convex Sparse Matrix Factorizations Francis R. Bach Julien Mairal Jean Ponce 201 143 0 10 Dec 2008