Graph Neural Ordinary Differential Equations

18 November 2019

Junyoung Park

Jinkyoo Park

Papers citing "Graph Neural Ordinary Differential Equations"

50 / 109 papers shown

Title
Inferring dynamic regulatory interaction graphs from time series data with perturbations Dhananjay Bhaskar Sumner Magruder E. Brouwer Aarthi Venkat Frederik Wenkel Guy Wolf Smita Krishnaswamy 17 3 0 13 Jun 2023
Learning the effective order of a hypergraph dynamical system Leonie Neuhäuser Michael Scholkemper Francesco Tudisco Michael T. Schaub 11 9 0 02 Jun 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 25 9 0 24 May 2023
Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems Lingbing Guo Wei-Qun Wang Zhuo Chen Ningyu Zhang Zequn Sun Yixuan Lai Qiang Zhang Huajun Chen 14 5 0 24 May 2023
A Fractional Graph Laplacian Approach to Oversmoothing Sohir Maskey Raffaele Paolino Aras Bacho Gitta Kutyniok 22 29 0 22 May 2023
Hawkes Process Based on Controlled Differential Equations Minju Jo Seung-Uk Kook Noseong Park AI4TS 31 1 0 09 May 2023
GNN-based physics solver for time-independent PDEs R. J. Gladstone H. Rahmani V. Suryakumar Hadi Meidani M. DÉlia A. Zareei AI4CE 20 15 0 28 Mar 2023
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 16 184 0 20 Mar 2023
Effectively Modeling Time Series with Simple Discrete State Spaces Michael Zhang Khaled Kamal Saab Michael Poli Tri Dao Karan Goel Christopher Ré AI4TS 22 44 0 16 Mar 2023
Framelet Message Passing Xinliang Liu Bingxin Zhou Chutian Zhang Yu Guang Wang 21 5 0 28 Feb 2023
Modulated Neural ODEs I. Auzina Çağatay Yıldız Sara Magliacane Matthias Bethge E. Gavves 20 5 0 26 Feb 2023
Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning Shivam Barwey Varun Shankar V. Viswanathan R. Maulik AI4CE 25 20 0 13 Feb 2023
TIDE: Time Derivative Diffusion for Deep Learning on Graphs M. Behmanesh Maximilian Krahn M. Ovsjanikov DiffM GNN 19 9 0 05 Dec 2022
GREAD: Graph Neural Reaction-Diffusion Networks Jeongwhan Choi Seoyoung Hong Noseong Park Sung-Bae Cho DiffM GNN 19 26 0 25 Nov 2022
Learning Modular Simulations for Homogeneous Systems Jayesh K. Gupta Sai H. Vemprala Ashish Kapoor 9 6 0 28 Oct 2022
torchode: A Parallel ODE Solver for PyTorch Marten Lienen Stephan Günnemann LRM 19 11 0 22 Oct 2022
Anti-Symmetric DGN: a stable architecture for Deep Graph Networks Alessio Gravina D. Bacciu Claudio Gallicchio GNN 14 50 0 18 Oct 2022
Modular Flows: Differential Molecular Generation Yogesh Verma Samuel Kaski Markus Heinonen Vikas K. Garg 23 14 0 12 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 70 13 0 08 Oct 2022
Gradient Gating for Deep Multi-Rate Learning on Graphs T. Konstantin Rusch B. Chamberlain Michael W. Mahoney Michael M. Bronstein Siddhartha Mishra 74 53 0 02 Oct 2022
Vectorized Adjoint Sensitivity Method for Graph Convolutional Neural Ordinary Differential Equations Jack Cai 11 0 0 14 Sep 2022
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous Variables Penglei Gao Xi Yang Rui Zhang Ping Guo John Y. Goulermas Kaizhu Huang AI4TS 13 4 0 03 Aug 2022
Structural Inference of Networked Dynamical Systems with Universal Differential Equations James Koch Zhao Chen Aaron Tuor Ján Drgoňa D. Vrabie PINN 24 10 0 11 Jul 2022
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications Sai Munikoti D. Agarwal L. Das M. Halappanavar Balasubramaniam Natarajan GNN OffRL AI4CE 27 57 0 16 Jun 2022
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition Yuelin Wang Kai Yi Xinliang Liu Yu Guang Wang Shi Jin 13 33 0 11 Jun 2022
Continuous Temporal Graph Networks for Event-Based Graph Data Jin Guo Zhen Han Zhou Su Jiliang Li Volker Tresp Yuyi Wang AI4CE 10 5 0 31 May 2022
Learning Interacting Dynamical Systems with Latent Gaussian Process ODEs Çağatay Yıldız M. Kandemir Barbara Rakitsch 46 10 0 24 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 59 39 0 16 May 2022
Learning Label Initialization for Time-Dependent Harmonic Extension A. Azad 25 1 0 03 May 2022
Graph Anisotropic Diffusion Ahmed A. A. Elhag Gabriele Corso Hannes Stärk Michael M. Bronstein DiffM GNN 17 0 0 30 Apr 2022
GCN-FFNN: A Two-Stream Deep Model for Learning Solution to Partial Differential Equations Onur Bilgin Thomas Vergutz S. Mehrkanoon GNN 9 3 0 28 Apr 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
Learning time-dependent PDE solver using Message Passing Graph Neural Networks Pourya Pilva A. Zareei AI4CE 25 6 0 15 Apr 2022
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks Marten Lienen Stephan Günnemann AI4TS 14 37 0 16 Mar 2022
Graph-Coupled Oscillator Networks T. Konstantin Rusch B. Chamberlain J. Rowbottom S. Mishra M. Bronstein 31 101 0 04 Feb 2022
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities Indranil Pan L. Mason Omar K. Matar AI4CE 36 45 0 07 Nov 2021
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
Beltrami Flow and Neural Diffusion on Graphs B. Chamberlain J. Rowbottom D. Eynard Francesco Di Giovanni Xiaowen Dong M. Bronstein AI4CE 32 79 0 18 Oct 2021
Robust and Scalable SDE Learning: A Functional Perspective Scott A. Cameron Tyron Cameron Arnu Pretorius Stephen J. Roberts 8 2 0 11 Oct 2021
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 25 55 0 10 Oct 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 28 64 0 02 Jul 2021
GRAND: Graph Neural Diffusion B. Chamberlain J. Rowbottom Maria I. Gorinova Stefan Webb Emanuele Rossi M. Bronstein GNN 22 253 0 21 Jun 2021
Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers Samuel C. Chevalier Jochen Stiasny Spyros Chatzivasileiadis 17 3 0 04 Jun 2021
Diffusion Mechanism in Residual Neural Network: Theory and Applications Tangjun Wang Zehao Dou Chenglong Bao Zuoqiang Shi DiffM 22 7 0 07 May 2021
Dissecting the Diffusion Process in Linear Graph Convolutional Networks Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin GNN 30 77 0 22 Feb 2021
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks Hao Tang Zhiao Huang Jiayuan Gu Bao-Liang Lu Hao Su AI4CE 15 9 0 26 Oct 2020
Neural Ordinary Differential Equations for Intervention Modeling Daehoon Gwak Gyuhyeon Sim Michael Poli Stefano Massaroli Jaegul Choo E. Choi 37 19 0 16 Oct 2020
TorchDyn: A Neural Differential Equations Library Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 6 24 0 20 Sep 2020
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 8 45 0 05 Aug 2020
Hypersolvers: Toward Fast Continuous-Depth Models Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park BDL AI4CE 8 46 0 19 Jul 2020