Alternatives and similar repositories for TabGNN

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

• nd7141 / bgnn
  ☆170Updated last year
• mwcvitkovic / Supervised-Learning-on-Relational-Databases-with-GNNs
  Code to reproduce the results in the paper Supervised Learning on Relational Databases with Graph Neural Networks.
  ☆63Updated 5 years ago
• JonathanCrabbe / Dynamask
  This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…
  ☆76Updated 3 years ago
• AstraZeneca / SubTab
  The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
  ☆145Updated 2 years ago
• Roytsai27 / awesome-GNN4TDL
  Graph Neural Networks for Tabular Data Learning (GNN4TDL)
  ☆96Updated last year
• vanderschaarlab / MIRACLE
  ☆28Updated last year
• jma712 / HyperSCI
  ☆45Updated last year
• maxiaoba / GRAPE
  ☆138Updated 4 years ago
• ioanabica / Time-Series-Deconfounder
  Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …
  ☆52Updated 4 years ago
• russchua / Graph-Isomorphism-Networks
  A Tensorflow 2.0 implementation of Graph Isomorphism Networks.
  ☆55Updated 6 years ago
• jsyoon0823 / VIME
  Codebase for VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain - NeurIPS 2020
  ☆148Updated 4 years ago
• marblet / GCNmf
  PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"
  ☆48Updated last year
• WilliamCCHuang / GraphLIME
  This is a Pytorch implementation of GraphLIME
  ☆92Updated 3 years ago
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆36Updated 3 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆61Updated 5 years ago
• sanatonek / time_series_explainability
  ☆61Updated 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
• gabrielspadon / ReGENN
  Recurrent Graph Evolution Neural Network (ReGENN) using Graph Soft Evolution (GSE)
  ☆30Updated 11 months ago
• AntonioLonga / Explaining-the-Explainers-in-Graph-Neural-Networks
  Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"
  ☆36Updated last year
• vunhatminh / PGMExplainer
  Generating PGM Explanation for GNN predictions
  ☆75Updated last year
• FilippoMB / Benchmark_dataset_for_graph_classification
  Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
  ☆49Updated 3 months ago
• dongkuanx27 / STAR
  Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs (IJCAI'19)
  ☆20Updated 3 years ago
• twitter-research / feature-propagation
  ☆82Updated 3 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 4 years ago
• yzhao062 / UOMS
  Resources and environment for unsupervised outlier model selection (UOMS)
  ☆24Updated 2 years ago
• kherud / neural-additive-models-pt
  PyTorch implementation for Neural Additive Models
  ☆23Updated 4 years ago
• maksym33 / FeatureImportanceDL
  ☆42Updated 2 years ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆90Updated last year
• wwweiwei / awesome-self-supervised-learning-for-tabular-data
  A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)
  ☆194Updated 4 months ago