Learning Differential Equations that are Easy to Solve

9 July 2020

Papers citing "Learning Differential Equations that are Easy to Solve"

50 / 79 papers shown

Title
Theoretical Guarantees for High Order Trajectory Refinement in Generative Flows Chengyue Gong Xiaoyu Li Yingyu Liang Jiangxuan Long Zhenmei Shi Zhao-quan Song Yu Tian 54 3 0 12 Mar 2025
HOFAR: High-Order Augmentation of Flow Autoregressive Transformers Yingyu Liang Zhizhou Sha Zhenmei Shi Zhao-quan Song Mingda Wan 75 1 0 11 Mar 2025
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations Grigory Bartosh Dmitry Vetrov C. A. Naesseth 76 0 0 04 Feb 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 42 0 0 12 Jan 2025
Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods Colby Fronk Linda R. Petzold 63 2 0 02 Dec 2024
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 63 2 0 20 Nov 2024
Training Stiff Neural Ordinary Differential Equations with Implicit Single-Step Methods Colby Fronk Linda R. Petzold 24 4 0 08 Oct 2024
The Extrapolation Power of Implicit Models Juliette Decugis Alicia Y. Tsai Max Emerling Ashwin Ganesh L. Ghaoui 34 0 0 19 Jul 2024
Nuclear Norm Regularization for Deep Learning Christopher Scarvelis Justin Solomon 23 1 0 23 May 2024
Zero-Shot Transfer of Neural ODEs Tyler Ingebrand Adam J. Thorpe Ufuk Topcu 26 3 0 14 May 2024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling Grigory Bartosh Dmitry Vetrov C. A. Naesseth DiffM 29 7 0 19 Apr 2024
Scaling physics-informed hard constraints with mixture-of-experts N. Chalapathi Yiheng Du Aditi Krishnapriyan AI4CE 32 12 0 20 Feb 2024
Sequential Flow Straightening for Generative Modeling Jongmin Yoon Juho Lee 27 0 0 09 Feb 2024
Rademacher Complexity of Neural ODEs via Chen-Fliess Series Joshua Hanson Maxim Raginsky 16 2 0 30 Jan 2024
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs Kevin Course P. Nair 24 3 0 16 Dec 2023
Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow Carlos E. Pérez De Jesús Alec J. Linot Michael D. Graham AI4CE 29 1 0 15 Dec 2023
On Tuning Neural ODE for Stability, Consistency and Faster Convergence Sheikh Waqas Akhtar ODL 16 0 0 04 Dec 2023
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator Learning Kuangdai Leng Mallikarjun Shankar Jeyan Thiyagalingam 26 2 0 01 Nov 2023
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature Alexander Norcliffe M. Deisenroth 23 3 0 21 Aug 2023
Trainability, Expressivity and Interpretability in Gated Neural ODEs T. Kim T. Can K. Krishnamurthy AI4CE 32 4 0 12 Jul 2023
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems Truong X. Nghiem Ján Drgoňa Colin N. Jones Zoltán Nagy Roland Schwan ... J. Paulson Andrea Carron M. Zeilinger Wenceslao Shaw-Cortez D. Vrabie PINN AI4CE 32 30 0 24 Jun 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair J R White Niki Kilbertus Maximilian Gelbrecht Niklas Boers 18 6 0 16 Jun 2023
Generalization bounds for neural ordinary differential equations and deep residual networks P. Marion 30 18 0 11 May 2023
Semi-Equivariant Conditional Normalizing Flows Eyal Rozenberg Daniel Freedman 22 0 0 13 Apr 2023
GECCO: Geometrically-Conditioned Point Diffusion Models M. Tyszkiewicz Pascal Fua Eduard Trulls DiffM 18 21 0 10 Mar 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 19 3 0 03 Mar 2023
Minimizing Trajectory Curvature of ODE-based Generative Models Sangyun Lee Beomsu Kim Jong Chul Ye 32 53 0 27 Jan 2023
Semi-Equivariant Continuous Normalizing Flows for Target-Aware Molecule Generation Eyal Rozenberg Daniel Freedman 19 0 0 09 Nov 2022
Sparsity in Continuous-Depth Neural Networks H. Aliee Till Richter Mikhail Solonin I. Ibarra Fabian J. Theis Niki Kilbertus 24 10 0 26 Oct 2022
GENIE: Higher-Order Denoising Diffusion Solvers Tim Dockhorn Arash Vahdat Karsten Kreis DiffM 41 104 0 11 Oct 2022
Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees Weijie Gan Chunwei Ying Parna Eshraghi Tongyao Wang C. Eldeniz Yuyang Hu Jiaming Liu Yasheng Chen H. An Ulugbek S. Kamilov 35 4 0 07 Oct 2022
Flow Matching for Generative Modeling Y. Lipman Ricky T. Q. Chen Heli Ben-Hamu Maximilian Nickel Matt Le OOD 41 1,036 0 06 Oct 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery Joon-Hyuk Ko Hankyul Koh Nojun Park W. Jhe 35 8 0 04 Oct 2022
Neural Integral Equations E. Zappala Antonio H. O. Fonseca J. O. Caro David van Dijk 25 10 0 30 Sep 2022
Survival Mixture Density Networks Xintian Han Mark Goldstein Rajesh Ranganath 21 5 0 23 Aug 2022
Adaptive Asynchronous Control Using Meta-learned Neural Ordinary Differential Equations Achkan Salehi Steffen Rühl Stéphane Doncieux AI4CE 11 2 0 25 Jul 2022
ICE-NODE: Integration of Clinical Embeddings with Neural Ordinary Differential Equations Asem Alaa Erik Mayer Mauricio Barahona AI4CE 14 3 0 05 Jul 2022
Conditional Permutation Invariant Flows Berend Zwartsenberg Adam Scibior Matthew Niedoba Vasileios Lioutas Yunpeng Liu Justice Sefas Setareh Dabiri J. Lavington Trevor Campbell Frank D. Wood 9 8 0 17 Jun 2022
On the balance between the training time and interpretability of neural ODE for time series modelling Yakov Golovanev A. Hvatov AI4TS 12 1 0 07 Jun 2022
Online Deep Equilibrium Learning for Regularization by Denoising Jiaming Liu Xiaojian Xu Weijie Gan S. Shoushtari Ulugbek S. Kamilov 26 26 0 25 May 2022
Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs Justin Baker Hedi Xia Yiwei Wang E. Cherkaev A. Narayan Long Chen Jack Xin Andrea L. Bertozzi Stanley J. Osher Bao Wang 14 5 0 19 Apr 2022
Deep Equilibrium Optical Flow Estimation Shaojie Bai Zhengyang Geng Yash Savani J. Zico Kolter 27 67 0 18 Apr 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed Shian Du Yihong Luo Wei-Neng Chen Jian Xu Delu Zeng 14 6 0 19 Mar 2022
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits Alan Yang J. Xiong Maxim Raginsky E. Rosenbaum AI4TS 16 4 0 14 Feb 2022
Continuous Deep Equilibrium Models: Training Neural ODEs faster by integrating them to Infinity Avik Pal Alan Edelman Chris Rackauckas 13 6 0 28 Jan 2022
Wassersplines for Neural Vector Field--Controlled Animation Paul Zhang Dmitriy Smirnov Justin Solomon 8 4 0 28 Jan 2022
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu AI4TS 14 17 0 14 Jan 2022
$$m^\ast$ of two-dimensional electron gas: a neural canonical transformation study$ $m^\ast$ of two-dimensional electron gas: a neural canonical transformation study H.-j. Xie Linfeng Zhang Lei Wang 20 8 0 10 Jan 2022
Neural Piecewise-Constant Delay Differential Equations Qunxi Zhu Yifei Shen Dongsheng Li Wei-Jer Lin PINN 20 6 0 04 Jan 2022
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 20 91 0 02 Nov 2021