Maximum Principle Based Algorithms for Deep Learning

26 October 2017

Papers citing "Maximum Principle Based Algorithms for Deep Learning"

40 / 40 papers shown

Title
Data Selection via Optimal Control for Language Models Yuxian Gu Li Dong Hongning Wang Y. Hao Qingxiu Dong Furu Wei Minlie Huang AI4CE 58 5 0 09 Oct 2024
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 33 1 0 04 Oct 2024
On Dissipativity of Cross-Entropy Loss in Training ResNets Jens Püttschneider T. Faulwasser 35 0 0 29 May 2024
Neural Delay Differential Equations: System Reconstruction and Image Classification Qunxi Zhu Yao Guo Wei Lin 25 32 0 11 Apr 2023
The Mori-Zwanzig formulation of deep learning D. Venturi Xiantao Li 25 1 0 12 Sep 2022
Neural Observer with Lyapunov Stability Guarantee for Uncertain Nonlinear Systems Song Chen Shengze Cai Tehuan Chen Chao Xu Jian Chu 24 5 0 27 Aug 2022
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems Qianxiao Li T. Lin Zuowei Shen 26 6 0 18 Aug 2022
Qualitative neural network approximation over R and C: Elementary proofs for analytic and polynomial activation Josiah Park Stephan Wojtowytsch 26 1 0 25 Mar 2022
Linear convergence of a policy gradient method for some finite horizon continuous time control problems C. Reisinger Wolfgang Stockinger Yufei Zhang 21 5 0 22 Mar 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed Shian Du Yihong Luo Wei Chen Jian Xu Delu Zeng 34 7 0 19 Mar 2022
Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models Ning Ding Yujia Qin Guang Yang Fu Wei Zonghan Yang ... Jianfei Chen Yang Liu Jie Tang Juan Li Maosong Sun 34 197 0 14 Mar 2022
Differential equation and probability inspired graph neural networks for latent variable learning Zhuangwei Shi 14 3 0 28 Feb 2022
Physics-informed neural networks via stochastic Hamiltonian dynamics learning Minh Nguyen Chandrajit Bajaj 21 1 0 15 Nov 2021
Deep Learning Approximation of Diffeomorphisms via Linear-Control Systems A. Scagliotti 29 13 0 24 Oct 2021
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities Wanyu Bian Yunmei Chen X. Ye 44 16 0 20 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 45 10 0 13 Sep 2021
Approximation capabilities of measure-preserving neural networks Aiqing Zhu Pengzhan Jin Yifa Tang 34 8 0 21 Jun 2021
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 34 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 29 133 0 22 Sep 2020
On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics E. Weinan Stephan Wojtowytsch MLT 18 53 0 30 Jul 2020
Machine Learning and Control Theory A. Bensoussan Yiqun Li Dinh Phan Cao Nguyen M. Tran S. Yam Xiang Zhou AI4CE 32 12 0 10 Jun 2020
Optimizing Neural Networks via Koopman Operator Theory Akshunna S. Dogra William T. Redman 19 50 0 03 Jun 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 32 52 0 27 May 2020
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees Jacob H. Seidman Mahyar Fazlyab V. Preciado George J. Pappas AAML 22 15 0 01 May 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
Analysis and applications of the residual varentropy of random lifetimes A. Di Crescenzo L. Paolillo 11 15 0 10 Mar 2020
Total Deep Variation for Linear Inverse Problems Erich Kobler Alexander Effland K. Kunisch Thomas Pock 19 89 0 14 Jan 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen David Duvenaud 17 310 0 05 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 33 102 0 30 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 46 1,002 0 22 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 30 107 0 22 Dec 2019
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 21 16 0 25 Oct 2019
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 40 31 0 28 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions Belinda Tzen Maxim Raginsky DiffM 26 99 0 05 Mar 2019
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 28 62 0 26 Sep 2018
A Mean-Field Optimal Control Formulation of Deep Learning Weinan E Jiequn Han Qianxiao Li OOD 14 182 0 03 Jul 2018
Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto E. Haber AI4CE 27 484 0 12 Apr 2018
An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks Qianxiao Li Shuji Hao 27 75 0 04 Mar 2018
Convolutional Neural Networks combined with Runge-Kutta Methods Mai Zhu Bo Chang Chong Fu AI4CE 41 52 0 24 Feb 2018