[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"
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Updated
Jun 16, 2024 - Python
[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"
Machine learning for molecular property prediction
Package for TwinBooster. Enables fast and powerful zero-shot molecular property prediction.
This repository is a brief tutorial about how Graph convolutional networks and message passing networks work with example code demonstration using pytorch and torch_geometric
Collection of Machine Learning and GNN methods for Molecular Property Prediction Task
Sort & Slice: A Simple and Superior Alternative to Hash-Based Folding for Extended-Connectivity Fingerprints
Exploring QSAR Models for Activity-Cliff Prediction
The official open-source repository for AutoMolDesigner, an easy-to-use Python application dedicated to automated molecular design.
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction. IJCAI 2024
MUBen: Benchmarking the Uncertainty of Molecular Representation Models
IUPAC-based large-scale molecular pre-trained model for property prediction and molecular generation
Pretraining Techniques for Graph Transformers
[ICML 2023] Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
An efficient curriculum learning-based strategy for molecular graph learning
3rd place solution for 2022 Samsung AI Challenge (Materials Discovery)
KDD-23 Automated 3D Pre-Training for Molecular Property Prediction
Code and Data for the paper: Graph Sampling-based Meta-Learning for Molecular Property Prediction [IJCAI2023]
Graduation Design
Predict optical properties of molecules with machine learning.
⚗️ Samsung AI Challenge for Scientific Discovery 5위 솔루션입니다.
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