Alternatives and similar repositories for ndcn

Users that are interested in ndcn are comparing it to the libraries listed below

• DeepGraphLearning / ContinuousGNN
  ☆47Updated 3 years ago
• ZijieH / CG-ODE
  ☆36Updated 3 years ago
• ZijieH / LG-ODE
  ☆33Updated 3 years ago
• kby24 / AIDD
  Automated Discovery of Interactions and Dynamics for Large Networked Dynamical Systems
  ☆16Updated 3 years ago
• cvignac / SMP
  ☆28Updated 3 years ago
• wokas36 / GraphSNN
  Graph Structured Neural Network
  ☆40Updated 2 years ago
• ebonilla / VGCN
  Variational Graph Convolutional Networks
  ☆23Updated 4 years ago
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆46Updated 3 years ago
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆43Updated 2 years ago
• hilbert9221 / NRI-MPM
  Code for Neural Relational Inference with Efficient Message Passing Mechanisms (AAAI 2021).
  ☆16Updated 4 years ago
• armanihm / GDC
  Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
  ☆60Updated 4 years ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆66Updated 3 years ago
• KarolisMart / DropGNN
  The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)
  ☆26Updated 2 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated 2 years ago
• RManLuo / GSNOP
  Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
  ☆34Updated 2 years ago
• flyingtango / DiGCL
  The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
  ☆35Updated 3 years ago
• zhongyu1998 / PG-GNN
  Official implementation of the ICML 2022 paper "Going Deeper into Permutation-Sensitive Graph Neural Networks"
  ☆27Updated 2 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆88Updated 3 years ago
• TaiLvYuanLiang / HGWaveNet
  ☆12Updated last year
• mgao97 / Higher-Order-Network
  ☆13Updated 5 months ago
• fishmoon1234 / DAG-NoCurl
  ☆25Updated 3 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆103Updated 3 years ago
• VGraphRNN / VGRNN
  Variational Graph Recurrent Neural Networks - PyTorch
  ☆116Updated 4 years ago
• CheriseZhu / GIL
  The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)
  ☆46Updated 4 years ago
• LiuChuang0059 / graph-pooling-papers
  IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
  ☆115Updated 2 months ago
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆45Updated 9 months ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 2 years ago
• xpuoxford / L2G-neurips2021
  ☆26Updated 3 years ago
• AaltoPML / Rethinking-pooling-in-GNNs
  ☆62Updated 4 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆167Updated last year