Title
Quantized Convolutional Neural Networks Through the Lens of Partial Differential EquationsResearch in the Mathematical Sciences (Res. Math. Sci.), 2021 Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 221 5 0 31 Aug 2021
Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs S. Dutta Peter Rivera-Casillas Orie M. Cecil Matthew W. Farthing E. Perracchione M. Putti AI4CE 132 9 0 06 Jul 2021
Learning ODEs via Diffeomorphisms for Fast and Robust Integration Weiming Zhi Tin Lai Lionel Ott Edwin V. Bonilla Fabio Ramos OOD 98 4 0 04 Jul 2021
Closed-form Continuous-time Neural ModelsNature Machine Intelligence (Nat. Mach. Intell.), 2021 Ramin Hasani Mathias Lechner Alexander Amini Lucas Liebenwein Aaron Ray Max Tschaikowski G. Teschl Daniela Rus PINN AI4TS 232 129 0 25 Jun 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 205 55 0 23 Jun 2021
Stateful ODE-Nets using Basis Function ExpansionsNeural Information Processing Systems (NeurIPS), 2021 A. Queiruga N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 196 17 0 21 Jun 2021
Causal Navigation by Continuous-time Neural Networks Charles J. Vorbach Ramin Hasani Alexander Amini Mathias Lechner Daniela Rus 179 54 0 15 Jun 2021
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics Shiqi Gong Qi Meng Yue Wang Lijun Wu Wei Chen Zhi-Ming Ma Tie-Yan Liu 223 4 0 08 Jun 2021
Learning Runge-Kutta Integration Schemes for ODE Simulation and Identification Said Ouala L. Debreu A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet 117 5 0 11 May 2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver HeuristicsInternational Conference on Machine Learning (ICML), 2021 Avik Pal Yingbo Ma Viral B. Shah Chris Rackauckas 161 41 0 09 May 2021
Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics S. Dutta Peter Rivera-Casillas Matthew W. Farthing AI4CE 129 14 0 22 Apr 2021
Stiff Neural Ordinary Differential EquationsChaos (Chaos), 2021 Suyong Kim Weiqi Ji Sili Deng Yingbo Ma Chris Rackauckas AI4CE 169 177 0 29 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit NetworksAAAI Conference on Artificial Intelligence (AAAI), 2021 Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 322 107 0 23 Mar 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan Oseledets 158 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 206 25 0 04 Mar 2021
Spline parameterization of neural network controls for deep learning Stefanie Günther Will Pazner Dongping Qi 90 4 0 27 Feb 2021
Learning orbital dynamics of binary black hole systems from gravitational wave measurementsPhysical Review Research (Phys. Rev. Res.), 2021 B. Keith Akshay Khadse Scott E. Field 126 12 0 25 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal MemoryNeural Information Processing Systems (NeurIPS), 2021 Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 138 27 0 19 Feb 2021
Momentum Residual Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 236 63 0 15 Feb 2021
Accelerating ODE-Based Neural Networks on Low-Cost FPGAsIEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPS), 2020 Hirohisa Watanabe Hiroki Matsutani 201 5 0 31 Dec 2020
Neural Closure Models for Dynamical SystemsProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Abhinav Gupta Pierre FJ Lermusiaux AI4CE 313 48 0 27 Dec 2020
Delay Differential Neural NetworksInternational Conference on Machine Learning Technologies (ICMLT), 2020 Srinivas Anumasa P. K. Srijith 117 6 0 12 Dec 2020
Faster Policy Learning with Continuous-Time GradientsConference on Learning for Dynamics & Control (L4DC), 2020 Samuel K. Ainsworth Kendall Lowrey John Thickstun Zaïd Harchaoui S. Srinivasa 233 13 0 12 Dec 2020
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics ProblemsProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Kookjin Lee E. Parish 183 82 0 28 Oct 2020
Differentiable Implicit Layers Andreas Look Simona Doneva M. Kandemir Rainer Gemulla Jan Peters 198 10 0 14 Oct 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 155 26 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 233 2 0 03 Sep 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 249 54 0 05 Aug 2020
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable ProjectionSIAM Journal on Mathematics of Data Science (SIMODS), 2020 Elizabeth Newman Lars Ruthotto Joseph L. Hart B. V. B. Waanders AAML 235 24 0 26 Jul 2020
MRI Image Reconstruction via Learning Optimization Using Neural ODEsInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020 Eric Z. Chen Terrence Chen Shanhui Sun 165 26 0 24 Jun 2020
A Shooting Formulation of Deep Learning François-Xavier Vialard Roland Kwitt Susan Wei Marc Niethammer 153 15 0 18 Jun 2020
On Second Order Behaviour in Augmented Neural ODEsNeural Information Processing Systems (NeurIPS), 2020 Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 224 105 0 12 Jun 2020
Liquid Time-constant Networks Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus Radu Grosu AI4TS AI4CE 228 313 0 08 Jun 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 383 156 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 192 47 0 05 Jun 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODEInternational Conference on Machine Learning (ICML), 2020 Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 211 121 0 03 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric DensitiesInternational Conference on Machine Learning (ICML), 2020 Jonas Köhler Leon Klein Frank Noé DRL 280 309 0 03 Jun 2020
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal TransportAAAI Conference on Artificial Intelligence (AAAI), 2020 Derek Onken Samy Wu Fung Xingjian Li Lars Ruthotto OT 469 189 0 29 May 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 241 59 0 27 May 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 409 599 0 18 May 2020
Neural Differential Equations for Single Image Super-resolutionInternational Conference on Learning Representations (ICLR), 2020 Teven Le Scao 123 2 0 02 May 2020
Towards Understanding Normalization in Neural ODEsInternational Conference on Learning Representations (ICLR), 2020 Julia Gusak L. Markeeva Talgat Daulbaev A. Katrutsa A. Cichocki Ivan Oseledets 209 19 0 20 Apr 2020
Bayesian differential programming for robust systems identification under uncertaintyProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Jianlong Wu Mohamed Aziz Bhouri P. Perdikaris OOD 256 36 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 120 6 0 07 Apr 2020
Deep connections between learning from limited labels & physical parameter estimation -- inspiration for regularization Bas Peters AI4CE 127 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 Oseledets 136 8 0 11 Mar 2020
Stochasticity in Neural ODEs: An Empirical StudyInternational Conference on Learning Representations (ICLR), 2020 V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 171 21 0 22 Feb 2020
Stochastic Normalizing Flows Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney BDL 125 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 350 688 0 13 Jan 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPUInternational Conference on Learning Representations (ICLR), 2020 Patrick Kidger Terry Lyons 165 94 0 03 Jan 2020

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ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs

International Joint Conference on Artificial Intelligence (IJCAI), 2019

27 February 2019

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

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Title
Quantized Convolutional Neural Networks Through the Lens of Partial Differential EquationsResearch in the Mathematical Sciences (Res. Math. Sci.), 2021 Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 221 5 0 31 Aug 2021
Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs S. Dutta Peter Rivera-Casillas Orie M. Cecil Matthew W. Farthing E. Perracchione M. Putti AI4CE 132 9 0 06 Jul 2021
Learning ODEs via Diffeomorphisms for Fast and Robust Integration Weiming Zhi Tin Lai Lionel Ott Edwin V. Bonilla Fabio Ramos OOD 98 4 0 04 Jul 2021
Closed-form Continuous-time Neural ModelsNature Machine Intelligence (Nat. Mach. Intell.), 2021 Ramin Hasani Mathias Lechner Alexander Amini Lucas Liebenwein Aaron Ray Max Tschaikowski G. Teschl Daniela Rus PINN AI4TS 232 129 0 25 Jun 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 205 55 0 23 Jun 2021
Stateful ODE-Nets using Basis Function ExpansionsNeural Information Processing Systems (NeurIPS), 2021 A. Queiruga N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 196 17 0 21 Jun 2021
Causal Navigation by Continuous-time Neural Networks Charles J. Vorbach Ramin Hasani Alexander Amini Mathias Lechner Daniela Rus 179 54 0 15 Jun 2021
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics Shiqi Gong Qi Meng Yue Wang Lijun Wu Wei Chen Zhi-Ming Ma Tie-Yan Liu 223 4 0 08 Jun 2021
Learning Runge-Kutta Integration Schemes for ODE Simulation and Identification Said Ouala L. Debreu A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet 117 5 0 11 May 2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver HeuristicsInternational Conference on Machine Learning (ICML), 2021 Avik Pal Yingbo Ma Viral B. Shah Chris Rackauckas 161 41 0 09 May 2021
Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics S. Dutta Peter Rivera-Casillas Matthew W. Farthing AI4CE 129 14 0 22 Apr 2021
Stiff Neural Ordinary Differential EquationsChaos (Chaos), 2021 Suyong Kim Weiqi Ji Sili Deng Yingbo Ma Chris Rackauckas AI4CE 169 177 0 29 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit NetworksAAAI Conference on Artificial Intelligence (AAAI), 2021 Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 322 107 0 23 Mar 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan Oseledets 158 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 206 25 0 04 Mar 2021
Spline parameterization of neural network controls for deep learning Stefanie Günther Will Pazner Dongping Qi 90 4 0 27 Feb 2021
Learning orbital dynamics of binary black hole systems from gravitational wave measurementsPhysical Review Research (Phys. Rev. Res.), 2021 B. Keith Akshay Khadse Scott E. Field 126 12 0 25 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal MemoryNeural Information Processing Systems (NeurIPS), 2021 Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 138 27 0 19 Feb 2021
Momentum Residual Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 236 63 0 15 Feb 2021
Accelerating ODE-Based Neural Networks on Low-Cost FPGAsIEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPS), 2020 Hirohisa Watanabe Hiroki Matsutani 201 5 0 31 Dec 2020
Neural Closure Models for Dynamical SystemsProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Abhinav Gupta Pierre FJ Lermusiaux AI4CE 313 48 0 27 Dec 2020
Delay Differential Neural NetworksInternational Conference on Machine Learning Technologies (ICMLT), 2020 Srinivas Anumasa P. K. Srijith 117 6 0 12 Dec 2020
Faster Policy Learning with Continuous-Time GradientsConference on Learning for Dynamics & Control (L4DC), 2020 Samuel K. Ainsworth Kendall Lowrey John Thickstun Zaïd Harchaoui S. Srinivasa 233 13 0 12 Dec 2020
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics ProblemsProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Kookjin Lee E. Parish 183 82 0 28 Oct 2020
Differentiable Implicit Layers Andreas Look Simona Doneva M. Kandemir Rainer Gemulla Jan Peters 198 10 0 14 Oct 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 155 26 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 233 2 0 03 Sep 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 249 54 0 05 Aug 2020
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable ProjectionSIAM Journal on Mathematics of Data Science (SIMODS), 2020 Elizabeth Newman Lars Ruthotto Joseph L. Hart B. V. B. Waanders AAML 235 24 0 26 Jul 2020
MRI Image Reconstruction via Learning Optimization Using Neural ODEsInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020 Eric Z. Chen Terrence Chen Shanhui Sun 165 26 0 24 Jun 2020
A Shooting Formulation of Deep Learning François-Xavier Vialard Roland Kwitt Susan Wei Marc Niethammer 153 15 0 18 Jun 2020
On Second Order Behaviour in Augmented Neural ODEsNeural Information Processing Systems (NeurIPS), 2020 Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 224 105 0 12 Jun 2020
Liquid Time-constant Networks Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus Radu Grosu AI4TS AI4CE 228 313 0 08 Jun 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 383 156 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 192 47 0 05 Jun 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODEInternational Conference on Machine Learning (ICML), 2020 Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 211 121 0 03 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric DensitiesInternational Conference on Machine Learning (ICML), 2020 Jonas Köhler Leon Klein Frank Noé DRL 280 309 0 03 Jun 2020
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal TransportAAAI Conference on Artificial Intelligence (AAAI), 2020 Derek Onken Samy Wu Fung Xingjian Li Lars Ruthotto OT 469 189 0 29 May 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 241 59 0 27 May 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 409 599 0 18 May 2020
Neural Differential Equations for Single Image Super-resolutionInternational Conference on Learning Representations (ICLR), 2020 Teven Le Scao 123 2 0 02 May 2020
Towards Understanding Normalization in Neural ODEsInternational Conference on Learning Representations (ICLR), 2020 Julia Gusak L. Markeeva Talgat Daulbaev A. Katrutsa A. Cichocki Ivan Oseledets 209 19 0 20 Apr 2020
Bayesian differential programming for robust systems identification under uncertaintyProceedings of the Royal Society A (Proc. R. Soc. A), 2020 Jianlong Wu Mohamed Aziz Bhouri P. Perdikaris OOD 256 36 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 120 6 0 07 Apr 2020
Deep connections between learning from limited labels & physical parameter estimation -- inspiration for regularization Bas Peters AI4CE 127 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 Oseledets 136 8 0 11 Mar 2020
Stochasticity in Neural ODEs: An Empirical StudyInternational Conference on Learning Representations (ICLR), 2020 V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 171 21 0 22 Feb 2020
Stochastic Normalizing Flows Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney BDL 125 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 350 688 0 13 Jan 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPUInternational Conference on Learning Representations (ICLR), 2020 Patrick Kidger Terry Lyons 165 94 0 03 Jan 2020

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