Chemical representation learning paper in Digital Discovery
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Updated
May 22, 2024 - Jupyter Notebook
Chemical representation learning paper in Digital Discovery
CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)
Open Knowledge Enrichment for Long-tail Entities, WWW 2020
An integrated Python package for molecular descriptor generation, data processing, model training, and hyper-parameter optimization.
Predicting properties of small molecules using MPNN on QM9 dataset
Machine learning algorithm implementation in materials science
EGAT - Edge Featured Graph Attention Networks for Property Prediction
Pittsburgh Single Family Home Prediction with Non-Conventional Data Streams
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