Alternatives and similar repositories for AIDD:

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

• calvin-zcx / ndcn
  Neural Dynamics on Complex Networks
  ☆51Updated 4 years ago
• hilbert9221 / NRI-MPM
  Code for Neural Relational Inference with Efficient Message Passing Mechanisms (AAAI 2021).
  ☆16Updated 3 years ago
• FilippoMB / The-expressive-power-of-pooling-in-GNNs
  Code and dataset to test empirically the expressive power of graph pooling operators.
  ☆35Updated last year
• tk-rusch / GraphCON
  GraphCON (ICML 2022)
  ☆59Updated 2 years ago
• ykiiiiii / ACMP
  ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks(ICLR 2023)
  ☆18Updated last year
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆65Updated 2 years ago
• armanihm / GDC
  Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
  ☆56Updated 4 years ago
• DeepGraphLearning / ContinuousGNN
  ☆46Updated 3 years ago
• marblet / GCNmf
  PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"
  ☆47Updated 11 months ago
• bnusss / GGN
  Gumbel Graph Network (GGN) : A General Deep Learning Framework for Network Reconstruction
  ☆70Updated 5 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆163Updated 11 months ago
• ytchx1999 / Graphormer
  This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
  ☆13Updated 3 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆53Updated last year
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆75Updated last year
• psanch21 / LCAT
  ☆20Updated last year
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆49Updated last year
• Graph-Machine-Learning-Group / sgp
  Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)
  ☆45Updated last year
• cvignac / SMP
  ☆26Updated 3 years ago
• FeiGSSS / Awesome-HigherOrderGraph
  Collection of papers relating data-driven higher-order graph/networks researches.
  ☆67Updated 2 years ago
• VGraphRNN / VGRNN
  Variational Graph Recurrent Neural Networks - PyTorch
  ☆114Updated 4 years ago
• xpuoxford / L2G-neurips2021
  ☆25Updated 3 years ago
• Kaixiong-Zhou / EGNN
  Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.
  ☆24Updated 3 years ago
• Graph-COM / ED-HNN
  [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
  ☆41Updated 5 months ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• TaiLvYuanLiang / HGWaveNet
  ☆12Updated 10 months ago
• jctops / understanding-oversquashing
  ☆41Updated 2 years ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆51Updated last year
• abiodun-ayodeji / Structure-Learning-from-Time-series-Data-with-CausalNex
  Time series data structure learning with NOTEARS and DYNOTEARS
  ☆11Updated 7 months ago
• Graph-COM / Neighborhood-Aware-Temporal-Network
  Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.
  ☆27Updated last year