most citedGeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2021★ 2 cited

GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning

Bumju Kwak, Jiwon Park, Taewon Kang +3

In recent years, molecular representation learning has emerged as a key area of focus in various chemical tasks. However, many existing models fail to fully consider the geometric…