LARS-research / TabGNNLinks
☆51Updated 4 years ago
Alternatives and similar repositories for TabGNN
Users that are interested in TabGNN are comparing it to the libraries listed below
Sorting:
- The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"☆150Updated 3 years ago
- ☆172Updated last year
- This is a Pytorch implementation of GraphLIME☆94Updated 4 years ago
- ☆45Updated last year
- Code to reproduce the results in the paper Supervised Learning on Relational Databases with Graph Neural Networks.☆63Updated 5 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Updated 3 years ago
- ☆146Updated 4 years ago
- Graph Neural Networks for Tabular Data Learning (GNN4TDL)☆110Updated 7 months ago
- Generating PGM Explanation for GNN predictions☆75Updated 2 years ago
- 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
- [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题☆111Updated last year
- A Tensorflow 2.0 implementation of Graph Isomorphism Networks.☆55Updated 6 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- ☆49Updated last year
- [ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions …☆26Updated 2 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- Source code for StageNet: Stage-Aware Neural Networks for Health Risk Prediction☆32Updated 9 months ago
- The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning I…☆120Updated last year
- ☆77Updated 4 years ago
- PyTorch implementation of "Graph Convolutional Networks for Graphs Containing Missing Features"☆49Updated 2 years ago
- ☆86Updated 3 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 5 years ago
- Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.☆51Updated 10 months ago
- Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch☆62Updated 5 years ago
- ☆39Updated 3 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆97Updated 2 years ago
- This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.039…☆124Updated 4 years ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 3 years ago
- ☆23Updated 2 years ago
- Codebase for VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain - NeurIPS 2020☆154Updated 5 years ago