kby24 / AIDD
Automated Discovery of Interactions and Dynamics for Large Networked Dynamical Systems
☆16Updated 3 years ago
Alternatives and similar repositories for AIDD:
Users that are interested in AIDD are comparing it to the libraries listed below
- Neural Dynamics on Complex Networks☆51Updated 4 years ago
- Code for Neural Relational Inference with Efficient Message Passing Mechanisms (AAAI 2021).☆16Updated 3 years ago
- Gumbel Graph Network (GGN) : A General Deep Learning Framework for Network Reconstruction☆70Updated 5 years ago
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆37Updated last year
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Updated 2 years ago
- GraphCON (ICML 2022)☆59Updated 2 years ago
- ☆27Updated 3 years ago
- Official Repository of "Graph Mixture Density Networks" (ICML 2021)☆26Updated 2 years ago
- Gradient gating (ICLR 2023)☆53Updated last year
- ☆13Updated 3 months ago
- ☆46Updated 3 years ago
- Pytorch implementation of XGNN☆10Updated 4 years ago
- ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)☆18Updated last year
- PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"☆47Updated last year
- ☆30Updated last year
- ☆20Updated last year
- An awesome collection of causality-inspired graph neural networks.☆70Updated 4 months ago
- Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch☆57Updated 4 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆101Updated 2 years ago
- Official implementation of the ICML 2022 paper "Going Deeper into Permutation-Sensitive Graph Neural Networks"☆27Updated 2 years ago
- ☆36Updated 3 years ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆63Updated last year
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- ☆26Updated 3 years ago
- ☆40Updated 2 years ago
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆16Updated last year
- Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)☆46Updated last year
- This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".☆13Updated 3 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 4 years ago