Kyle Swanson
Kyle Swanson
Потвърден имейл адрес: stanford.edu - Начална страница
A deep learning approach to antibiotic discovery
JM Stokes, K Yang, K Swanson, W Jin, A Cubillos-Ruiz, NM Donghia, ...
Cell 180 (4), 688-702. e13, 2020
Analyzing learned molecular representations for property prediction
K Yang, K Swanson, W Jin, C Coley, P Eiden, H Gao, A Guzman-Perez, ...
Journal of chemical information and modeling 59 (8), 3370-3388, 2019
Mammographic breast density assessment using deep learning: clinical implementation
CD Lehman, A Yala, T Schuster, B Dontchos, M Bahl, K Swanson, ...
Radiology 290 (1), 52-58, 2019
Uncertainty quantification using neural networks for molecular property prediction
L Hirschfeld, K Swanson, K Yang, R Barzilay, CW Coley
Journal of Chemical Information and Modeling 60 (8), 3770-3780, 2020
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
G Liu, DB Catacutan, K Rathod, K Swanson, W Jin, JC Mohammed, ...
Nature Chemical Biology 19 (11), 1342-1350, 2023
From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou
Cell, 2023
Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens
Z Wu, AE Trevino, E Wu, K Swanson, HJ Kim, HB D’Angio, R Preska, ...
Nature Biomedical Engineering 6 (12), 1435-1448, 2022
Rationalizing text matching: Learning sparse alignments via optimal transport
K Swanson, L Yu, T Lei
arXiv preprint arXiv:2005.13111, 2020
Deep learning for automated classification and characterization of amorphous materials
K Swanson, S Trivedi, J Lequieu, K Swanson, R Kondor
Soft matter 16 (2), 435-446, 2020
Improving molecular design by stochastic iterative target augmentation
K Yang, W Jin, K Swanson, R Barzilay, T Jaakkola
International Conference on Machine Learning, 10716-10726, 2020
Message passing neural networks for molecular property prediction
K Swanson
Massachusetts Institute of Technology, 2019
7-UP: Generating in silico CODEX from a small set of immunofluorescence markers
E Wu, AE Trevino, Z Wu, K Swanson, HJ Kim, HB D’Angio, R Preska, ...
PNAS nexus 2 (6), pgad171, 2023
Building a Production Model for Retrieval-Based Chatbots
K Swanson, L Yu, C Fox, J Wohlwend, T Lei
1st Workshop on NLP for Conversational AI at the 57th Annual Meeting of the …, 2019
Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN
Y Rosen, M Brbić, Y Roohani, K Swanson, Z Li, J Leskovec
Nature Methods, 1-9, 2024
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics
K Swanson, G Liu, DB Catacutan, A Arnold, J Zou, JM Stokes
Nature Machine Intelligence 6 (3), 338-353, 2024
SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles
Z Wu, AE Trevino, E Wu, K Swanson, HJ Kim, HB D’Angio, R Preska, ...
bioRxiv, 2022.05. 12.491707, 2022
ADMET-AI: A machine learning ADMET platform for evaluation of large-scale chemical libraries
K Swanson, P Walther, J Leitz, S Mukherjee, JC Wu, RV Shivnaraine, ...
bioRxiv, 2023.12. 28.573531, 2023
File matching with rationale alignment using neural networks and an optimal transport algorithm
K Swanson, L Yu, T Lei
US Patent 11,238,278, 2022
Predicting Immune Escape with Pretrained Protein Language Model Embeddings
K Swanson, H Chang, J Zou
Machine Learning in Computational Biology, 110-130, 2022
Monte Carlo Tree Search for Interpreting Stress in Natural Language
K Swanson, J Hsu, M Suzgun
arXiv preprint arXiv:2204.08105, 2022
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