Stable Architectures for Deep Neural Networks

9 May 2017

Papers citing "Stable Architectures for Deep Neural Networks"

43 / 143 papers shown

Title
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Philip Torr Vinay P. Namboodiri BDL AI4TS 27 74 0 18 Jun 2020
A block coordinate descent optimizer for classification problems exploiting convexity Ravi G. Patel N. Trask Mamikon A. Gulian E. Cyr ODL 30 7 0 17 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 36 90 0 12 Jun 2020
Neural Ordinary Differential Equations on Manifolds Luca Falorsi Patrick Forré BDL AI4CE 14 33 0 11 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 33 23 0 10 Jun 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
Fractional Deep Neural Network via Constrained Optimization Harbir Antil R. Khatri R. Löhner Deepanshu Verma 30 29 0 01 Apr 2020
Stable Neural Flows Stefano Massaroli Michael Poli Michelangelo Bin Jinkyoo Park Atsushi Yamashita Hajime Asama 46 31 0 18 Mar 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
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 296 0 07 Feb 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
A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks Zhaodong Chen Lei Deng Bangyan Wang Guoqi Li Yuan Xie 35 28 0 01 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 33 102 0 30 Dec 2019
ODE-based Deep Network for MRI Reconstruction A. Yazdanpanah O. Afacan Simon K. Warfield OOD 15 3 0 27 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 25 107 0 22 Dec 2019
Multilevel Initialization for Layer-Parallel Deep Neural Network Training E. Cyr Stefanie Günther J. Schroder AI4CE 22 11 0 19 Dec 2019
Graph Neural Ordinary Differential Equations Michael Poli Stefano Massaroli Junyoung Park Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 51 154 0 18 Nov 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
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 32 30 0 22 Oct 2019
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment Ruben Hühnerbein Fabrizio Savarino Stefania Petra Christoph Schnörr 16 11 0 22 Oct 2019
ANODEV2: A Coupled Neural ODE Evolution Framework Tianjun Zhang Z. Yao A. Gholami Kurt Keutzer Joseph E. Gonzalez George Biros Michael W. Mahoney 14 41 0 10 Jun 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 23 136 0 09 Jun 2019
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series E. Brouwer Jaak Simm Adam Arany Yves Moreau SyDa CML AI4TS 45 290 0 29 May 2019
Neural-networks for geophysicists and their application to seismic data interpretation Bas Peters E. Haber J. Granek AI4CE 22 36 0 27 Mar 2019
IMEXnet: A Forward Stable Deep Neural Network E. Haber Keegan Lensink Eran Treister Lars Ruthotto 36 40 0 06 Mar 2019
Towards Robust ResNet: A Small Step but A Giant Leap Jingfeng Zhang Bo Han L. Wynter K. H. Low Mohan Kankanhalli 24 41 0 28 Feb 2019
ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs A. Gholami Kurt Keutzer George Biros 30 166 0 27 Feb 2019
Particle Flow Bayes' Rule Xinshi Chen H. Dai Le Song 14 9 0 02 Feb 2019
PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network Zichao Long Yiping Lu Bin Dong AI4CE 31 543 0 30 Nov 2018
Forward Stability of ResNet and Its Variants Linan Zhang Hayden Schaeffer 30 47 0 24 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 31 618 0 02 Nov 2018
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 17 62 0 26 Sep 2018
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network A. Sherstinsky 39 3,603 0 09 Aug 2018
A Mean-Field Optimal Control Formulation of Deep Learning Weinan E Jiequn Han Qianxiao Li OOD 14 182 0 03 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 101 4,954 0 19 Jun 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 19 75 0 04 Mar 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 25 74 0 22 Feb 2018
The exploding gradient problem demystified - definition, prevalence, impact, origin, tradeoffs, and solutions George Philipp D. Song J. Carbonell ODL 35 46 0 15 Dec 2017
Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang Lili Meng E. Haber Lars Ruthotto David Begert E. Holtham AI4CE 30 261 0 12 Sep 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016