Code for The Catalyst Deep Neural Networks (Cat-DNNs) in Singlet Fission Property Prediction
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Updated
Aug 31, 2021 - Python
Code for The Catalyst Deep Neural Networks (Cat-DNNs) in Singlet Fission Property Prediction
Samsung AI Challenge for Scientific Discovery, Samsung Advanced Institute of Technology and Dacon, ~2021.09.27
🥇Samsung AI Challenge 2021 1등 솔루션입니다🥇
Molecular-property prediction with sparsity
The code base for AWARE, a graph representation learning method published at TMLR
Official implementation of pre-training via denoising for TorchMD-NET
An atom-bond transformer-based message passing neural network for molecular property prediction.
This repository contains codes and data related to the paper "FunQG: Molecular Representation Learning Via Quotient Graphs". A pre-print version of this paper is currently available at
⚗️ Samsung AI Challenge for Scientific Discovery 5위 솔루션입니다.
Predict optical properties of molecules with machine learning.
Graduation Design
Code and Data for the paper: Graph Sampling-based Meta-Learning for Molecular Property Prediction [IJCAI2023]
KDD-23 Automated 3D Pre-Training for Molecular Property Prediction
3rd place solution for 2022 Samsung AI Challenge (Materials Discovery)
An efficient curriculum learning-based strategy for molecular graph learning
[ICML 2023] Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
Pretraining Techniques for Graph Transformers
IUPAC-based large-scale molecular pre-trained model for property prediction and molecular generation
MUBen: Benchmarking the Uncertainty of Molecular Representation Models
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction. IJCAI 2024
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