yangnianzu0515 / MoleOODView external linksLinks
Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).
☆62Feb 16, 2023Updated 2 years ago
Alternatives and similar repositories for MoleOOD
Users that are interested in MoleOOD are comparing it to the libraries listed below
Sorting:
- Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)☆23Oct 16, 2023Updated 2 years ago
- We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.☆105Feb 23, 2023Updated 2 years ago
- The official implementation of our paper "MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Lea…☆67Jun 8, 2023Updated 2 years ago
- Official implementation for GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs (NeurIPS 20…☆20Oct 14, 2022Updated 3 years ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Aug 25, 2024Updated last year
- OOD Dataset Curator and Benchmark for AI-aided Drug Discovery☆169Oct 23, 2022Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆121Aug 28, 2023Updated 2 years ago
- [SIGKDD 2023] HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline☆22Jun 16, 2023Updated 2 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆207Feb 21, 2025Updated 11 months ago
- Structure-based out-of-distribution (OOD) material property prediction: a benchmark study☆15May 17, 2025Updated 8 months ago
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆84Jul 27, 2023Updated 2 years ago
- New structural distributional shifts for evaluating graph models☆15Oct 25, 2023Updated 2 years ago
- Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)☆210Sep 20, 2022Updated 3 years ago
- [NeurIPS 2022 Spotlight] Improving Generative Adversarial Networks via Adversarial Learning in Latent Space☆17Nov 20, 2022Updated 3 years ago
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆172Oct 8, 2023Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Nov 24, 2022Updated 3 years ago
- Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"☆127Aug 18, 2023Updated 2 years ago
- ☆15Mar 16, 2023Updated 2 years ago
- A curated list of resources for OOD detection with graph data.☆19Dec 30, 2023Updated 2 years ago
- source code of AAAI 2024 paper "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization".☆18Apr 29, 2024Updated last year
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Jun 28, 2023Updated 2 years ago
- AI for a cure, a combination of Latent-GAN and VAE-JTNN to create 100% valid drug like molecules☆10Mar 16, 2020Updated 5 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Nov 4, 2024Updated last year
- [AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"☆33Sep 14, 2024Updated last year
- The official implementation for "Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment" which is accepted to NeurIP…☆22May 7, 2024Updated last year
- Code for ICML21 paper "Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation"☆12Feb 8, 2023Updated 3 years ago
- Code for AAAI21 paper "Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning"☆11Feb 15, 2022Updated 4 years ago
- The official source code for "Shift-Robust Molecular Relational Learning with Causal Substructure"☆24May 31, 2023Updated 2 years ago
- [ICLR 2023] "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules"☆129Jun 9, 2023Updated 2 years ago
- Notebook for standardization of actvity data, nonadditivity analysis and its evaluation.☆12Mar 16, 2023Updated 2 years ago
- Semi-supervised Junction Tree Variational Autoencoder for jointly trained property prediction and molecule structure generation. (AAAI 23…☆12Jan 14, 2023Updated 3 years ago
- ☆11Feb 26, 2024Updated last year
- Sequence-based protein solubility predictor☆11Apr 1, 2020Updated 5 years ago
- DSResSol: A sequence-based solubility predictor created with Dilated Squeeze Excitation Residual Networks☆11May 30, 2024Updated last year
- ☆12Jul 3, 2021Updated 4 years ago
- Source code and documentation of a specialized computer assisted synthesis planning (CASP) tool used for the deconstruction of ring syste…☆12May 25, 2020Updated 5 years ago
- 基于SG2300X的视频检索【使用自然语言搜索视频内容，定位到符合描述的具体时间段】☆13Feb 29, 2024Updated last year
- Sequence-based protein solubility prediction using multidimensional embedding☆12Apr 19, 2021Updated 4 years ago
- [NeurIPS 2023] Implementation of "Improving Self-supervised Molecular Representation Learning using Persistent Homology"☆12Nov 16, 2023Updated 2 years ago