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06/26/2023
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generation
Molecular conformer generation (MCG) is an important task in cheminforma...
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09/02/2021
Characterizing possible failure modes in physics-informed neural networks
Recent work in scientific machine learning has developed so-called physi...
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11/10/2020
Topological Regularization via Persistence-Sensitive Optimization
Optimization, a key tool in machine learning and statistics, relies on r...
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10/30/2020
PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction
Understanding protein structure-function relationships is a key challeng...
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10/01/2020
Persistent homology advances interpretable machine learning for nanoporous materials
Machine learning for nanoporous materials design and discovery has emerg...
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01/16/2020