361 citations · 931 across the 14 of their papers we have counts for
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q-bio.QM2021
Neural Distance Embeddings for Biological Sequences
Gabriele Corso, Rex Ying, Michal Pándy +3
The development of data-dependent heuristics and representations for biological sequences that reflect their evolutionary distance is critical for large-scale biological research.…
cs.LG2021★ 85 cited
3D Infomax improves GNNs for Molecular Property Prediction
Hannes Stärk, Dominique Beaini, Gabriele Corso +4
Molecular property prediction is one of the fastest-growing applications of deep learning with critical real-world impacts. Including 3D molecular structure as input to learned mod…