ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs

27 February 2019

Papers citing "ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs"

48 / 98 papers shown

Title
Stiff Neural Ordinary Differential Equations Suyong Kim Weiqi Ji Sili Deng Yingbo Ma Chris Rackauckas AI4CE 11 143 0 29 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit Networks Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 35 84 0 23 Mar 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan V. Oseledets 11 2 0 15 Mar 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 20 20 0 04 Mar 2021
Spline parameterization of neural network controls for deep learning Stefanie Günther Will Pazner Dongping Qi 13 3 0 27 Feb 2021
Learning orbital dynamics of binary black hole systems from gravitational wave measurements B. Keith Akshay Khadse Scott E. Field 23 8 0 25 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 20 23 0 19 Feb 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 24 56 0 15 Feb 2021
Accelerating ODE-Based Neural Networks on Low-Cost FPGAs Hirohisa Watanabe Hiroki Matsutani 14 4 0 31 Dec 2020
Neural Closure Models for Dynamical Systems Abhinav Gupta Pierre FJ Lermusiaux AI4CE 19 45 0 27 Dec 2020
Delay Differential Neural Networks Srinivas Anumasa P. K. Srijith 14 5 0 12 Dec 2020
Faster Policy Learning with Continuous-Time Gradients Samuel K. Ainsworth Kendall Lowrey John Thickstun Zaïd Harchaoui S. Srinivasa 19 11 0 12 Dec 2020
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems Kookjin Lee E. Parish 8 65 0 28 Oct 2020
Differentiable Implicit Layers Andreas Look Simona Doneva M. Kandemir Rainer Gemulla Jan Peters 24 9 0 14 Oct 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 11 23 0 07 Oct 2020
A Practical Layer-Parallel Training Algorithm for Residual Networks Qi Sun Hexin Dong Zewei Chen Weizhen Dian Jiacheng Sun Yitong Sun Zhenguo Li Bin Dong ODL 17 2 0 03 Sep 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 18 45 0 05 Aug 2020
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection Elizabeth Newman Lars Ruthotto Joseph L. Hart B. V. B. Waanders AAML 28 19 0 26 Jul 2020
MRI Image Reconstruction via Learning Optimization Using Neural ODEs Eric Z. Chen Terrence Chen Shanhui Sun 33 23 0 24 Jun 2020
A Shooting Formulation of Deep Learning François-Xavier Vialard Roland Kwitt Susan Wei Marc Niethammer 13 13 0 18 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lió 28 90 0 12 Jun 2020
Liquid Time-constant Networks Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus Radu Grosu AI4TS AI4CE 16 215 0 08 Jun 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 22 127 0 08 Jun 2020
Structure preserving deep learning E. Celledoni Matthias Joachim Ehrhardt Christian Etmann R. McLachlan B. Owren Carola-Bibiane Schönlieb Ferdia Sherry AI4CE 15 43 0 05 Jun 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 58 110 0 03 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler Leon Klein Frank Noé DRL 18 258 0 03 Jun 2020
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport Derek Onken Samy Wu Fung Xingjian Li Lars Ruthotto OT 10 156 0 29 May 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 24 51 0 27 May 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 25 449 0 18 May 2020
Neural Differential Equations for Single Image Super-resolution Teven Le Scao 9 2 0 02 May 2020
Towards Understanding Normalization in Neural ODEs Julia Gusak L. Markeeva Talgat Daulbaev A. Katrutsa A. Cichocki Ivan V. Oseledets 11 19 0 20 Apr 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 25 32 0 15 Apr 2020
Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs Giorgio Giannone Asha Anoosheh A. Quaglino P. DÓro Marco Gallieri Jonathan Masci AI4TS 12 6 0 07 Apr 2020
Deep connections between learning from limited labels & physical parameter estimation -- inspiration for regularization Bas Peters AI4CE 16 0 0 17 Mar 2020
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs Talgat Daulbaev A. Katrutsa L. Markeeva Julia Gusak A. Cichocki Ivan V. Oseledets 9 8 0 11 Mar 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 22 20 0 22 Feb 2020
Stochastic Normalizing Flows Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney BDL 6 1 0 21 Feb 2020
Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas Yingbo Ma Julius Martensen Collin Warner K. Zubov R. Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman AI4CE 33 569 0 13 Jan 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU Patrick Kidger Terry Lyons 29 83 0 03 Jan 2020
ODE-based Deep Network for MRI Reconstruction A. Yazdanpanah O. Afacan Simon K. Warfield OOD 10 3 0 27 Dec 2019
Neural ODEs for Image Segmentation with Level Sets Rafael Valle F. Reda M. Shoeybi P. LeGresley Andrew Tao Bryan Catanzaro 9 8 0 25 Dec 2019
Graph Neural Ordinary Differential Equations Michael Poli Stefano Massaroli Junyoung Park Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 42 154 0 18 Nov 2019
NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data Yifan Sun Linan Zhang Hayden Schaeffer AI4TS 14 91 0 08 Aug 2019
Approximation Capabilities of Neural ODEs and Invertible Residual Networks Han Zhang Xi Gao Jacob Unterman Tom Arodz 11 98 0 30 Jul 2019
SNODE: Spectral Discretization of Neural ODEs for System Identification A. Quaglino Marco Gallieri Jonathan Masci Jan Koutník AI4TS 16 48 0 17 Jun 2019
ANODEV2: A Coupled Neural ODE Evolution Framework Tianjun Zhang Z. Yao A. Gholami Kurt Keutzer Joseph E. Gonzalez George Biros Michael W. Mahoney 9 41 0 10 Jun 2019
Fully Hyperbolic Convolutional Neural Networks Keegan Lensink Bas Peters E. Haber MedIm 29 18 0 24 May 2019
Deep learning as optimal control problems: models and numerical methods Martin Benning E. Celledoni Matthias Joachim Ehrhardt B. Owren Carola-Bibiane Schönlieb 11 80 0 11 Apr 2019