Alpha Lee
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Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction
P Schwaller, T Laino, T Gaudin, P Bolgar, CA Hunter, C Bekas, AA Lee
ACS central science 5 (9), 1572-1583, 2019
Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning
Y Zhang, Q Tang, Y Zhang, J Wang, U Stimming, AA Lee
Nature Communications 11, 1706, 2020
The electrostatic screening length in concentrated electrolytes increases with concentration
AM Smith, AA Lee, S Perkin
The journal of physical chemistry letters 7 (12), 2157-2163, 2016
Long range electrostatic forces in ionic liquids
MA Gebbie, AM Smith, HA Dobbs, GG Warr, X Banquy, M Valtiner, ...
Chemical communications 53 (7), 1214-1224, 2017
Predicting materials properties without crystal structure: deep representation learning from stoichiometry
REA Goodall, AA Lee
Nature communications 11 (1), 6280, 2020
Scaling analysis of the screening length in concentrated electrolytes
AA Lee, CS Perez-Martinez, AM Smith, S Perkin
Physical review letters 119 (2), 026002, 2017
SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids
J Jansen, KC Reimer, JS Nagai, FS Varghese, GJ Overheul, M de Beer, ...
Cell stem cell 29 (2), 217-231. e8, 2022
Underscreening in concentrated electrolyes
AA Lee, C Perez-Martinez, AM Smith, S Perkin
Underscreening in concentrated electrolytes
AA Lee, C Perez-Martinez, AM Smith, S Perkin
Faraday Discussions, 2017
Are room-temperature ionic liquids dilute electrolytes?
AA Lee, D Vella, S Perkin, A Goriely
The journal of physical chemistry letters 6 (1), 159-163, 2015
Alternative radical pairs for cryptochrome-based magnetoreception
AA Lee, JCS Lau, HJ Hogben, T Biskup, DR Kattnig, PJ Hore
Journal of The Royal Society Interface 11 (95), 20131063, 2014
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning
Y Zhang
Chemical science 10 (35), 8154-8163, 2019
Learning the molecular grammar of protein condensates from sequence determinants and embeddings
KL Saar, AS Morgunov, R Qi, WE Arter, G Krainer, AA Lee, TPJ Knowles
Proceedings of the National Academy of Sciences 118 (15), e2019053118, 2021
Molecular transformer unifies reaction prediction and retrosynthesis across pharma chemical space
AA Lee, Q Yang, V Sresht, P Bolgar, X Hou, JL Klug-McLeod, CR Butler
Chemical Communications 55 (81), 12152-12155, 2019
Crowdsourcing drug discovery for pandemics
J Chodera, AA Lee, N London, F von Delft
Nature Chemistry 12 (7), 581-581, 2020
Impedance-based forecasting of lithium-ion battery performance amid uneven usage
PK Jones, U Stimming, AA Lee
Nature Communications 13 (1), 4806, 2022
Switching the structural force in ionic liquid-solvent mixtures by varying composition
AM Smith, AA Lee, S Perkin
Physical Review Letters 118 (9), 096002, 2017
Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning
Y Zhang, AM Saxe, MS Advani, AA Lee
Molecular Physics 116 (21-22), 3214-3223, 2018
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
DP Kovács, W McCorkindale, AA Lee
Nature communications 12 (1), 1695, 2021
Single-file charge storage in conducting nanopores
AA Lee, S Kondrat, AA Kornyshev
Physical review letters 113 (4), 048701, 2014
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