Awesome Graph Neural Differential Equations

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ODE

1. [2024] A Fractional Graph Laplacian Approach to Oversmoothing [paper]
2. [2024] A Recurrent Spatio-Temporal Graph Neural Network Based on Latent Time Graph for Multi-Channel Time Series Forecasting [paper]
3. [2024] A framework based on physics-informed graph neural ODE: for continuous spatial-temporal pandemic prediction [paper]
4. [2024] AGC-ODE: Adaptive Graph Controlled Neural ODE for Human Mobility Prediction [paper]
5. [2024] Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution [paper]
6. [2024] Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach [paper]
7. [2024] An embedding model for temporal knowledge graphs with long and irregular intervals [paper]
8. [2024] Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation [paper]
9. [2024] BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations [paper]
10. [2024] Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems [paper]
11. [2024] Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting [paper]
12. [2024] Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendation [paper]
13. [2024] DuSEGO: Dual Second-order Equivariant Graph Ordinary Differential Equation [paper]
14. [2024] Dynamic Graph Neural Ordinary Differential Equation Network for Multi-modal Emotion Recognition in Conversation [paper]
15. [2024] Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems [paper]
16. [2024] Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph [paper]
17. [2024] Graph Fourier Neural ODEs: Bridging Spatial and Temporal Multiscales in Molecular Dynamics [paper]
18. [2024] Graph Neural Aggregation-diffusion with Metastability [paper]
19. [2024] Graph Neural Ordinary Differential Equations for Coarse-Grained Socioeconomic Dynamics [paper]
20. [2024] Graph Spring Neural ODEs for Link Sign Prediction [paper]
21. [2024] HYPERGRAPH DYNAMIC SYSTEM [paper]
22. [2024] Incorporating Domain Differential Equations into Graph Convolutional Networks to Lower Generalization Discrepancy [paper]
23. [2024] Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations [paper]
24. [2024] Information Diffusion Prediction with Graph Neural Ordinary Differential Equation Network [paper]
25. [2024] Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction [paper]
26. [2024] Learning Graph ODE for Continuous-Time Sequential Recommendation [paper]
27. [2024] Learning System Dynamics without Forgetting [paper]
28. [2024] Adding attention to the neural ordinary differential equation for spatio-temporal prediction [paper]
29. [2024] Link prediction by continuous spatiotemporal representation via neural differential equations [paper]
30. [2024] Liquid-Graph Time-Constant Network for Multi-Agent Systems Control [paper]
31. [2024] Long Range Propagation on Continuous-Time Dynamic Graphs [paper]
32. [2024] MPSTAN: Metapopulation-Based Spatio–Temporal Attention Network for Epidemic Forecasting [paper]
33. [2024] Missing Data Imputation via Neighbor Data Feature-Enriched Neural Ordinary Differential Equations [paper]
34. [2024] Modelling Networked Dynamical System by Temporal Graph Neural ODE with Irregularly Partial Observed Time-series Data [paper]
35. [2024] Neural Symbolic Regression of Complex Network Dynamics [paper]
36. [2024] On The Temporal Domain of Differential Equation Inspired Graph Neural Networks [paper]
37. [2024] PGODE: Towards High-quality System Dynamics Modeling [paper]
38. [2024] PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction [paper]
39. [2024] Physics-informed Neural ODE for Post-disaster Mobility Recovery [paper]
40. [2024] Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton in Hyperbolic Space [paper]
41. [2024] Predicting Time Series of Networked Dynamical Systems without Knowing Topology [paper]
42. [2024] R-ODE: Ricci Curvature Tells When You Will be Informed [paper]
43. [2024] SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases [paper]
44. [2024] SEGODE: a structure-enhanced graph neural ordinary differential equation network model for temporal link prediction [paper]
45. [2024] STEMFold: Stochastic Temporal Manifold for Multi-Agent Interactions in the Presence of Hidden Agents [paper]
46. [2024] Second-Order Graph ODEs for Multi-Agent Trajectory Forecasting [paper]
47. [2024] Siamese learning based on graph differential equation for Next-POI recommendation [paper]
48. [2024] Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-Time Dynamics [paper]
49. [2024] Spatio-temporal envolutional graph neural network for traffic flow prediction in UAV-based urban traffic monitoring system [paper]
50. [2024] Temporal Graph ODEs for Irregularly-Sampled Time Series [paper]
51. [2024] Towards complex dynamic physics system simulation with graph neural ordinary equations [paper]
52. [2024] Unleashing the Power of High-pass Filtering in Continuous Graph Neural Networks [paper]
53. [2024] NODE-SAT: TEMPORAL GRAPH LEARNING WITH NEURAL ODE-GUIDED SELF-ATTENTION [paper]
54. [2024] PURE: Prompt Evolution with Graph ODE for Out-of-distribution Fluid Dynamics Modeling [paper]
55. [2024] EGODE: An Event-attended Graph ODE Framework for Modeling Rigid Dynamics [paper]
56. [2024] Neural Ordinary Differential Equations for Modeling Epidemic Spreading [paper]
57. [2024] Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion [paper]
58. [2023] ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition [paper]
59. [2023] Anti-Symmetric DGN: a stable architecture for Deep Graph Networks [paper]
60. [2023] Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction [paper]
61. [2023] CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems [paper]
62. [2023] CoordiNet: Constrained Dynamics Learning for State Coordination Over Graph [paper]
63. [2023] Diffusion Graph Neural Ordinary Differential Equation Network for Traffic Prediction [paper]
64. [2023] Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction [paper]
65. [2023] Feature Transportation Improves Graph Neural Networks [paper]
66. [2023] GREAD: Graph Neural Reaction-Diffusion Networks [paper]
67. [2023] Generalizing Graph ODE for Learning Complex System Dynamics across Environments [paper]
68. [2023] Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering [paper]
69. [2023] Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting [paper]
70. [2023] HDG-ODE: A Hierarchical Continuous-Time Model for Human Pose Forecasting [paper]
71. [2023] HOPE: High-order Graph ODE For Modeling Interacting Dynamics [paper]
72. [2023] Learning Latent ODEs With Graph RNN for Multi-Channel Time Series Forecasting [paper]
73. [2023] Learning continuous dynamic network representation with transformer-based temporal graph neural network [paper]
74. [2023] Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting [paper]
75. [2023] MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEs [paper]
76. [2023] Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs [paper]
77. [2023] Reaction-Diffusion Graph Ordinary Differential Equation Networks: Traffic-Law-Informed Speed Prediction under Mismatched Data [paper]
78. [2023] Spatio-Temporal Hypergraph Neural ODE Network for Traffic Forecasting [paper]
79. [2023] Structure-Enhanced Graph Neural ODE Network for Temporal Link Prediction [paper]
80. [2023] TANGO: Time-Reversal Latent GraphODE for Multi-Agent Dynamical Systems [paper]
81. [2023] Temporal Branching-Graph Neural ODE without Prior Structure for Traffic Flow Forecasting [paper]
82. [2023] Temporal Graph Neural Networks for Irregular Data [paper]
83. [2023] Temporal super-resolution traffic flow forecasting via continuous-time network dynamics [paper]
84. [2023] Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs [paper]
85. [2023] Climate modeling with neural advection–diffusion equation [paper]
86. [2022] CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting [paper]
87. [2022] Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendation [paper]
88. [2022] GRAND++: GRAPH NEURAL DIFFUSION WITH A SOURCE TERM [paper]
89. [2022] Graph ODE Recurrent Neural Networks for Traffic Flow Forecasting [paper]
90. [2022] Graph-Coupled Oscillator Networks [paper]
91. [2022] Heterogeneous Graph Convolutional Network-Based Dynamic Rumor Detection on Social Media [paper]
92. [2022] Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks [paper]
93. [2022] Learning Modular Simulations for Homogeneous Systems [paper]
94. [2022] Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs [paper]
95. [2022] Neural ordinary differential equation control of dynamics on graphs [paper]
96. [2022] Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations [paper]
97. [2022] Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems [paper]
98. [2021] CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph [paper]
99. [2021] ConTIG: Continuous Representation Learning on Temporal Interaction Graphs [paper]
100. [2021] Continuous-Depth Neural Models for Dynamic Graph Prediction [paper]
101. [2021] Coupled Graph ODE for Learning Interacting System Dynamics [paper]
102. [2021] GRAND: Graph Neural Diffusion [paper]
103. [2021] Inductive and irregular dynamic network representation based on ordinary differential equations [paper]
104. [2021] LT-OCF: Learnable-Time ODE-based Collaborative Filtering [paper]
105. [2021] Learning Neural Ordinary Equations for Forecasting Future Links on Temporal Knowledge Graphs [paper]
106. [2021] STR-GODEs: Spatial-Temporal-Ridership Graph ODEs for Metro Ridership Prediction [paper]
107. [2021] Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting [paper]
108. [2021] Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems [paper] 109 [2021] Climate Modeling with Neural Diffusion Equations [paper]
109. [2020] Continuous Graph Neural Networks [paper]
110. [2020] Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations [paper]
111. [2020] Neural Dynamics on Complex Networks [paper]
112. [2019] Graph Neural Ordinary Differential Equations [paper]

PDE

1. [2024] Continuous Spiking Graph Neural Networks [paper]
2. [2024] Feature Transportation Improves Graph Neural Networks [paper]
3. [2024] Graph Neural Reaction Diffusion Models [paper]
4. [2024] HAMLET: Graph Transformer Neural Operator for Partial Differential Equations [paper]
5. [2022] Modular Flows: Differential Molecular Generation [paper]
6. [2021] Beltrami Flow and Neural Diffusion on Graphs [paper]
7. [2021] GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations [paper]
8. [2021] Learning continuous-time PDEs from sparse data with graph neural networks [paper]

SDE

1. [2024] BROGNET: MOMENTUM CONSERVING GRAPH NEU- RAL STOCHASTIC DIFFERENTIAL EQUATION FOR LEARNING BROWNIAN DYNAMICS [paper]
2. [2024] Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatiotemporal Forecasting [paper]
3. [2024] Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations [paper]
4. [2024] Evolved Differential Model for Sporadic Graph Time-Series Prediction [paper]
5. [2024] AGGDN: A Continuous Stochastic Predictive Model for Monitoring Sporadic Time Series on Graphs [paper]
6. [2023] Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation [paper]
7. [2023] Graph Neural Stochastic Differential Equations [paper]
8. [2022] GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation [paper]

Others Graph Neural DEs

Controlled Differential Equation (CDE)

1. [2023] Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations [paper]
2. [2022] Graph Neural Controlled Differential Equations for Traffic Forecasting [paper]

Rough Differential Equation (RDE)

1. [2023] Graph Neural Rough Differential Equations for Traffic Forecasting [paper]

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