ChemBERTa: large-scale self-supervised pretraining for molecular property prediction S Chithrananda, G Grand, B Ramsundar NeurIPS 2020 ML for Molecules Workshop, 2020 | 439* | 2020 |
Chemberta-2: Towards chemical foundation models W Ahmad, E Simon, S Chithrananda, G Grand, B Ramsundar ELLIS Machine Learning for Molecule Discovery Workshop, 2022 | 110* | 2022 |
Assigning confidence to molecular property prediction AK Nigam, R Pollice, MFD Hurley, RJ Hickman, M Aldeghi, N Yoshikawa, ... Expert opinion on drug discovery 16 (9), 1009-1023, 2021 | 51 | 2021 |
TOPH (True Retrieval Of Proteins Homologs): Adapting A Contrastive Question-Answering Framework for Protein Search R Boger, A Lu, S Chithrananda, K Yang, P Skopintsev, B Adler, E Wallace, ... ICML Workshop for Computational Biology 2023, 2023 | 2 | 2023 |
RNA language models predict mutations that improve RNA function Y Shulgina, MI Trinidad, CJ Langeberg, H Nisonoff, S Chithrananda, ... bioRxiv, 2024 | 1 | 2024 |
Functional protein mining with conformal guarantees RS Boger, S Chithrananda, AN Angelopoulos, PH Yoon, MH Jordan, ... bioRxiv, 2024 | | 2024 |
Successive Weight Regularization for Plasticity in Deep Reinforcement Learning V Teo, A Rajaraman, S Chithrananda | | |