Title
VNODE: A Piecewise Continuous Volterra Neural Network Siddharth Roheda Aniruddha Bala Rohit Chowdhury Rohan Jaiswal 104 0 0 29 Sep 2025
Reversible Deep Equilibrium Models Sam McCallum Kamran Arora James Foster 175 2 0 16 Sep 2025
Latent Stochastic Interpolants Saurabh Singh Dmitry Lagun DiffM BDL 171 1 0 02 Jun 2025
Rex: Reversible Solvers for Diffusion Models Zander W. Blasingame Chen Liu DiffM 278 0 0 12 Feb 2025
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 405 8 0 15 Oct 2024
DFM: Interpolant-free Dual Flow Matching Denis A. Gudovskiy Tomoyuki Okuno Yohei Nakata AI4CE 204 0 0 11 Oct 2024
PGODE: Towards High-quality System Dynamics ModelingInternational Conference on Machine Learning (ICML), 2023 Xiao Luo Yiyang Gu Huiyu Jiang Hang Zhou Jinsheng Huang Wei Ju Zhiping Xiao Ming Zhang Luke Huan AI4CE 218 8 0 11 Nov 2023
Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations S. Lim Jaehyeon Park Seojin Kim Hyowon Wi Haksoo Lim Jinsung Jeon Jeongwhan Choi Noseong Park AI4TS AI4CE 217 2 0 08 Nov 2023
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 146 5 0 21 Aug 2023
Embracing the chaos: analysis and diagnosis of numerical instability in variational flowsNeural Information Processing Systems (NeurIPS), 2023 Zuheng Xu Trevor Campbell 170 6 0 12 Jul 2023
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical SystemsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2023 Ce Zhang Kailiang Wu Zhihai He 165 0 0 15 Apr 2023
Semi-Equivariant Conditional Normalizing Flows Eyal Rozenberg Daniel Freedman 155 0 0 13 Apr 2023
Learning Subgrid-scale Models with Neural Ordinary Differential Equations Shinhoo Kang Emil M. Constantinescu AI4CE 239 7 0 20 Dec 2022
Semi-Equivariant Continuous Normalizing Flows for Target-Aware Molecule Generation Eyal Rozenberg Daniel Freedman 177 1 0 09 Nov 2022
Prediction-based One-shot Dynamic Parking PricingInternational Conference on Information and Knowledge Management (CIKM), 2022 Seoyoung Hong H. Shin Jeongwhan Choi Noseong Park 127 5 0 30 Aug 2022
Closed-Form Diffeomorphic Transformations for Time Series AlignmentInternational Conference on Machine Learning (ICML), 2022 Iñigo Martinez E. Viles Igor García Olaizola AI4TS 141 11 0 16 Jun 2022
A memory-efficient neural ODE framework based on high-level adjoint differentiationIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Hong Zhang Wenjun Zhao 170 5 0 02 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?Neural Information Processing Systems (NeurIPS), 2022 Michael E. Sander Pierre Ablin Gabriel Peyré 237 33 0 29 May 2022
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and ForecastingThe Web Conference (WWW), 2022 Sheo Yon Jhin Jaehoon Lee Minju Jo Seung-Uk Kook Jinsung Jeon Jihyeon Hyeong Jayoung Kim Noseong Park AI4TS 214 27 0 19 Apr 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving SpeedComputer Vision and Pattern Recognition (CVPR), 2022 Shian Du Yihong Luo Wei Chen Jian Xu Delu Zeng 226 9 0 19 Mar 2022
Characteristic Neural Ordinary Differential EquationsInternational Conference on Learning Representations (ICLR), 2021 Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 334 3 0 25 Nov 2021
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies Bao Wang Hedi Xia T. Nguyen Stanley Osher AI4CE 146 11 0 13 Oct 2021
Heavy Ball Neural Ordinary Differential EquationsNeural Information Processing Systems (NeurIPS), 2021 Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 176 69 0 10 Oct 2021
Second-Order Neural ODE Optimizer Guan-Horng Liu T. Chen Evangelos A. Theodorou 138 18 0 29 Sep 2021
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting Sheo Yon Jhin H. Shin Seoyoung Hong Solhee Park Noseong Park AI4TS 168 32 0 04 Sep 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
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 213 55 0 23 Jun 2021
Distributional Gradient Matching for Learning Uncertain Neural Dynamics ModelsNeural Information Processing Systems (NeurIPS), 2021 Lenart Treven Philippe Wenk Florian Dorfler Andreas Krause OOD 165 2 0 22 Jun 2021
Neural Controlled Differential Equations for Online Prediction Tasks James Morrill Patrick Kidger Lingyi Yang Terry Lyons AI4TS 178 51 0 21 Jun 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processesConference on Uncertainty in Artificial Intelligence (UAI), 2021 Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 220 19 0 21 Jun 2021
Efficient and Accurate Gradients for Neural SDEsNeural Information Processing Systems (NeurIPS), 2021 Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 317 80 0 27 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
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal MemoryNeural Information Processing Systems (NeurIPS), 2021 Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 146 27 0 19 Feb 2021

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MALI: A memory efficient and reverse accurate integrator for Neural ODEs

International Conference on Learning Representations (ICLR), 2021

9 February 2021

James S. Duncan

Papers citing "MALI: A memory efficient and reverse accurate integrator for Neural ODEs"

33 / 33 papers shown

Title
VNODE: A Piecewise Continuous Volterra Neural Network Siddharth Roheda Aniruddha Bala Rohit Chowdhury Rohan Jaiswal 104 0 0 29 Sep 2025
Reversible Deep Equilibrium Models Sam McCallum Kamran Arora James Foster 175 2 0 16 Sep 2025
Latent Stochastic Interpolants Saurabh Singh Dmitry Lagun DiffM BDL 171 1 0 02 Jun 2025
Rex: Reversible Solvers for Diffusion Models Zander W. Blasingame Chen Liu DiffM 278 0 0 12 Feb 2025
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 405 8 0 15 Oct 2024
DFM: Interpolant-free Dual Flow Matching Denis A. Gudovskiy Tomoyuki Okuno Yohei Nakata AI4CE 204 0 0 11 Oct 2024
PGODE: Towards High-quality System Dynamics ModelingInternational Conference on Machine Learning (ICML), 2023 Xiao Luo Yiyang Gu Huiyu Jiang Hang Zhou Jinsheng Huang Wei Ju Zhiping Xiao Ming Zhang Luke Huan AI4CE 218 8 0 11 Nov 2023
Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations S. Lim Jaehyeon Park Seojin Kim Hyowon Wi Haksoo Lim Jinsung Jeon Jeongwhan Choi Noseong Park AI4TS AI4CE 217 2 0 08 Nov 2023
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 146 5 0 21 Aug 2023
Embracing the chaos: analysis and diagnosis of numerical instability in variational flowsNeural Information Processing Systems (NeurIPS), 2023 Zuheng Xu Trevor Campbell 170 6 0 12 Jul 2023
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical SystemsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2023 Ce Zhang Kailiang Wu Zhihai He 165 0 0 15 Apr 2023
Semi-Equivariant Conditional Normalizing Flows Eyal Rozenberg Daniel Freedman 155 0 0 13 Apr 2023
Learning Subgrid-scale Models with Neural Ordinary Differential Equations Shinhoo Kang Emil M. Constantinescu AI4CE 239 7 0 20 Dec 2022
Semi-Equivariant Continuous Normalizing Flows for Target-Aware Molecule Generation Eyal Rozenberg Daniel Freedman 177 1 0 09 Nov 2022
Prediction-based One-shot Dynamic Parking PricingInternational Conference on Information and Knowledge Management (CIKM), 2022 Seoyoung Hong H. Shin Jeongwhan Choi Noseong Park 127 5 0 30 Aug 2022
Closed-Form Diffeomorphic Transformations for Time Series AlignmentInternational Conference on Machine Learning (ICML), 2022 Iñigo Martinez E. Viles Igor García Olaizola AI4TS 141 11 0 16 Jun 2022
A memory-efficient neural ODE framework based on high-level adjoint differentiationIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Hong Zhang Wenjun Zhao 170 5 0 02 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?Neural Information Processing Systems (NeurIPS), 2022 Michael E. Sander Pierre Ablin Gabriel Peyré 237 33 0 29 May 2022
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and ForecastingThe Web Conference (WWW), 2022 Sheo Yon Jhin Jaehoon Lee Minju Jo Seung-Uk Kook Jinsung Jeon Jihyeon Hyeong Jayoung Kim Noseong Park AI4TS 214 27 0 19 Apr 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving SpeedComputer Vision and Pattern Recognition (CVPR), 2022 Shian Du Yihong Luo Wei Chen Jian Xu Delu Zeng 226 9 0 19 Mar 2022
Characteristic Neural Ordinary Differential EquationsInternational Conference on Learning Representations (ICLR), 2021 Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 334 3 0 25 Nov 2021
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies Bao Wang Hedi Xia T. Nguyen Stanley Osher AI4CE 146 11 0 13 Oct 2021
Heavy Ball Neural Ordinary Differential EquationsNeural Information Processing Systems (NeurIPS), 2021 Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 176 69 0 10 Oct 2021
Second-Order Neural ODE Optimizer Guan-Horng Liu T. Chen Evangelos A. Theodorou 138 18 0 29 Sep 2021
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting Sheo Yon Jhin H. Shin Seoyoung Hong Solhee Park Noseong Park AI4TS 168 32 0 04 Sep 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
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 213 55 0 23 Jun 2021
Distributional Gradient Matching for Learning Uncertain Neural Dynamics ModelsNeural Information Processing Systems (NeurIPS), 2021 Lenart Treven Philippe Wenk Florian Dorfler Andreas Krause OOD 165 2 0 22 Jun 2021
Neural Controlled Differential Equations for Online Prediction Tasks James Morrill Patrick Kidger Lingyi Yang Terry Lyons AI4TS 178 51 0 21 Jun 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processesConference on Uncertainty in Artificial Intelligence (UAI), 2021 Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 220 19 0 21 Jun 2021
Efficient and Accurate Gradients for Neural SDEsNeural Information Processing Systems (NeurIPS), 2021 Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 317 80 0 27 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
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal MemoryNeural Information Processing Systems (NeurIPS), 2021 Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 146 27 0 19 Feb 2021