Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 931 papers shown

Title
Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression Alexander Norcliffe Lev Proleev Diana Mincu F. Hartsell Katherine A. Heller Subhrajit Roy 34 2 0 15 Feb 2023
Learning to Simulate Daily Activities via Modeling Dynamic Human Needs Yuan Yuan Huandong Wang Jingtao Ding Depeng Jin Yong Li AI4TS AI4CE 14 30 0 09 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories Bas Peters 32 0 0 09 Feb 2023
Flow Matching on General Geometries Ricky T. Q. Chen Y. Lipman AI4CE 27 67 0 07 Feb 2023
Eigen-informed NeuralODEs: Dealing with stability and convergence issues of NeuralODEs Tobias Thummerer Lars Mikelsons 19 3 0 07 Feb 2023
Differentiable Programming of Chemical Reaction Networks A. Mordvintsev E. Randazzo Eyvind Niklasson 6 0 0 06 Feb 2023
Using Intermediate Forward Iterates for Intermediate Generator Optimization Harshit Mishra Jurijs Nazarovs Manmohan Dogra Sathya Ravi DiffM 27 0 0 05 Feb 2023
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation Rui Xue Haoyu Han MohamadAli Torkamani Jian Pei Xiaorui Liu GNN 31 19 0 03 Feb 2023
Learning PDE Solution Operator for Continuous Modeling of Time-Series Yesom Park Jaemoo Choi Changyeon Yoon Changhoon Song Myung-joo Kang AI4TS AI4CE 27 3 0 02 Feb 2023
MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEs Theodor Westny Joel Oskarsson Björn Olofsson Erik Frisk 35 31 0 01 Feb 2023
Self-Consistent Velocity Matching of Probability Flows Lingxiao Li Samuel Hurault Justin Solomon 29 12 0 31 Jan 2023
Continuous Spatiotemporal Transformers Antonio H. O. Fonseca E. Zappala J. O. Caro David van Dijk 26 7 0 31 Jan 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network Yang Sun Yifan Xie BDL CML 34 1 0 28 Jan 2023
Minimizing Trajectory Curvature of ODE-based Generative Models Sangyun Lee Beomsu Kim Jong Chul Ye 37 53 0 27 Jan 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui Tom S. Bertalan George J. Pappas M. Morari Ioannis G. Kevrekidis Mahyar Fazlyab AAML 21 2 0 27 Jan 2023
Learning the Dynamics of Sparsely Observed Interacting Systems Linus Bleistein Adeline Fermanian A. Jannot Agathe Guilloux 38 5 0 27 Jan 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 39 27 0 26 Jan 2023
Solving Inverse Physics Problems with Score Matching Benjamin Holzschuh S. Vegetti Nils Thuerey DiffM 13 10 0 24 Jan 2023
Inference of Continuous Linear Systems from Data with Guaranteed Stability P. Goyal I. P. Duff P. Benner 14 4 0 24 Jan 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space Model Zhidi Lin Feng Yin Juan Maroñas 28 7 0 21 Jan 2023
Generalized Neural Closure Models with Interpretability Abhinava Gupta Pierre FJ Lermusiaux AI4CE 22 9 0 15 Jan 2023
Stretched and measured neural predictions of complex network dynamics V. Vasiliauskaite Nino Antulov-Fantulin 25 1 0 12 Jan 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences Chaopeng Shen A. Appling Pierre Gentine Toshiyuki Bandai H. Gupta ... Chris Rackauckas Tirthankar Roy Chonggang Xu Binayak Mohanty K. Lawson AI4CE 34 14 0 10 Jan 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control Adam J. Thorpe Cyrus Neary Franck Djeumou Meeko Oishi Ufuk Topcu 32 7 0 09 Jan 2023
Deep Learning and Computational Physics (Lecture Notes) Deep Ray Orazio Pinti Assad A. Oberai PINN AI4CE 21 7 0 03 Jan 2023
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation Han Huang Leilei Sun Bowen Du Weifeng Lv 45 40 0 01 Jan 2023
Selected aspects of complex, hypercomplex and fuzzy neural networks A. Niemczynowicz R. Kycia Maciej Jaworski A. Siemaszko J. Calabuig ... Baruch Schneider Diana Berseghyan Irina Perfiljeva V. Novák Piotr Artiemjew 19 0 0 29 Dec 2022
Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators Yannik P. Wotte Sven Dummer N. Botteghi C. Brune Stefano Stramigioli Federico Califano 36 5 0 29 Dec 2022
Continuous Depth Recurrent Neural Differential Equations Srinivas Anumasa Geetakrishnasai Gunapati P. K. Srijith AI4TS 26 0 0 28 Dec 2022
A Mathematical Framework for Learning Probability Distributions Hongkang Yang 26 7 0 22 Dec 2022
The Underlying Correlated Dynamics in Neural Training Rotem Turjeman Tom Berkov I. Cohen Guy Gilboa 19 3 0 18 Dec 2022
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent Richard Archibald F. Bao Yanzhao Cao Hui‐Jie Sun 52 2 0 17 Dec 2022
Asymptotic Analysis of Deep Residual Networks R. Cont Alain Rossier Renyuan Xu 27 4 0 15 Dec 2022
Temporal Weights Adam A. Kohan E. Rietman H. Siegelmann 14 0 0 13 Dec 2022
A Neural ODE Interpretation of Transformer Layers Yaofeng Desmond Zhong Tongtao Zhang Amit Chakraborty Biswadip Dey 20 9 0 12 Dec 2022
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management Muneeza Azmat Malvern Madondo Kelsey L. DiPietro R. Horesh Arun Bawa Michael Jacobs Raghavan Srinivasan Fearghal O'Donncha 19 4 0 12 Dec 2022
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series Futoon M. Abushaqra Hao Xue Yongli Ren Flora D. Salim AI4TS 26 2 0 07 Dec 2022
TIDE: Time Derivative Diffusion for Deep Learning on Graphs M. Behmanesh Maximilian Krahn M. Ovsjanikov DiffM GNN 24 9 0 05 Dec 2022
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation Han Huang Leilei Sun Bowen Du Yanjie Fu Weifeng Lv DiffM 32 42 0 04 Dec 2022
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints Jianyi Yang Shaolei Ren 20 2 0 03 Dec 2022
Nonlinear controllability and function representation by neural stochastic differential equations Tanya Veeravalli Maxim Raginsky DiffM 11 2 0 01 Dec 2022
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks Cyrus Neary Ufuk Topcu PINN AI4CE 18 12 0 01 Dec 2022
Applications of Lattice Gauge Equivariant Neural Networks Matteo Favoni A. Ipp David I. Müller 14 6 0 01 Dec 2022
Proximal Residual Flows for Bayesian Inverse Problems J. Hertrich BDL TPM 33 4 0 30 Nov 2022
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer Damjan Kalajdzievski Ximeng Mao Pascal Fortier-Poisson Guillaume Lajoie Blake A. Richards AI4TS 10 3 0 29 Nov 2022
Physics-informed Neural Networks with Unknown Measurement Noise Philipp Pilar Niklas Wahlström PINN 23 6 0 28 Nov 2022
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions Luca Thiede Chong Sun A. Aspuru‐Guzik 24 1 0 27 Nov 2022
Latent Space Diffusion Models of Cryo-EM Structures Karsten Kreis Tim Dockhorn Zihao Li Ellen D. Zhong DiffM 30 15 0 25 Nov 2022
Normalizing Flow with Variational Latent Representation Hanze Dong Shizhe Diao Weizhong Zhang Tong Zhang BDL OOD DRL 8 0 0 21 Nov 2022
Exploring Physical Latent Spaces for High-Resolution Flow Restoration Chloé Paliard Nils Thuerey Kiwon Um AI4CE 23 0 0 21 Nov 2022