AIPI-590-XAI / Duke-AI-XAILinks
This is a repository for Duke's AI MEng course, AIPI 590, Emerging Trends in XAI
☆19Updated 7 months ago
Alternatives and similar repositories for Duke-AI-XAI
Users that are interested in Duke-AI-XAI are comparing it to the libraries listed below
Sorting:
- The official source code for "Conditional Graph Information Bottleneck for Molecular Relational Learning".☆44Updated 2 years ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆101Updated last year
- The offical source code for [2024 NeurIPS] "Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge"☆34Updated 7 months ago
- Learning to Group Auxiliary Datasets for Molecule, NeurIPS2023☆18Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆58Updated 2 years ago
- ☆15Updated 2 years ago
- All graph/GNN papers accepted at NeurIPS 2024.☆85Updated last year
- Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022)…☆62Updated 2 years ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆24Updated 2 years ago
- Code implementation for paper "Can Large Language Models Empower Molecular Property Prediction?"☆39Updated 2 years ago
- GNNExplainer implementation using DGL☆31Updated 4 years ago
- Project for the prediction of drug side-effect occurrences in the general population with Graph Neural Networks.☆10Updated last year
- Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"☆127Updated 2 years ago
- ☆25Updated 3 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆205Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 3 years ago
- Code for the papers: "Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach", "A Meta-Learning Approach for Gra…☆18Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆207Updated 11 months ago
- ☆57Updated 3 years ago
- The offical source code for [2023 NeurIPS] " Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transfor…☆30Updated last year
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆14Updated last year
- [NeurIPS 2023] "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules"☆40Updated last year
- Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation☆35Updated 2 years ago
- The official source code for "Shift-Robust Molecular Relational Learning with Causal Substructure"☆24Updated 2 years ago
- ☆33Updated last year
- [KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"☆47Updated 10 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆174Updated last year
- This repository contains a PyTorch implementation of the paper "Hierarchical Graph Representation Learning for the Prediction of Drug-Tar…☆12Updated 3 years ago
- ALL Molecular ML papers from NeurIPS'24.☆64Updated last year
- Explanation method for Graph Neural Networks (GNNs)☆71Updated 9 months ago