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Kevin P Greenman

Showing results (1-10 of 7) with videos related to

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Chemical Science|February 25, 2022
Multi-fidelity prediction of molecular optical peaks with deep learningKevin P Greenman, William H Green, Rafael Gómez-Bombarelli
Plos Computational Biology|January 8, 2025
Benchmarking uncertainty quantification for protein engineeringKevin P Greenman, Ava P Amini, Kevin K Yang
Chemical Science|May 14, 2025
Symmetry-constrained generation of diverse low-bandgap molecules with Monte Carlo tree searchAkshay Subramanian, James Damewood, Juno Nam, et al.
Chemical Science|November 21, 2025
A unified active learning framework for photosensitizer designYizhe Chen, Shomik Verma, Kevin P Greenman, et al.
Journal of Chemical Information and Modeling|December 26, 2023
Chemprop: A Machine Learning Package for Chemical Property PredictionEsther Heid, Kevin P Greenman, Yunsie Chung, et al.
Journal of Chemical Information and Modeling|December 26, 2025
Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property PredictionDavid E Graff, Nathan K Morgan, Jackson W Burns, et al.
Science (New York, N.Y.)|December 21, 2023
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and backBrent A Koscher, Richard B Canty, Matthew A McDonald, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Chemical Science|February 25, 2022
Multi-fidelity prediction of molecular optical peaks with deep learningKevin P Greenman, William H Green, Rafael Gómez-Bombarelli
Plos Computational Biology|January 8, 2025
Benchmarking uncertainty quantification for protein engineeringKevin P Greenman, Ava P Amini, Kevin K Yang
Chemical Science|May 14, 2025
Symmetry-constrained generation of diverse low-bandgap molecules with Monte Carlo tree searchAkshay Subramanian, James Damewood, Juno Nam, et al.
Chemical Science|November 21, 2025
A unified active learning framework for photosensitizer designYizhe Chen, Shomik Verma, Kevin P Greenman, et al.
Journal of Chemical Information and Modeling|December 26, 2023
Chemprop: A Machine Learning Package for Chemical Property PredictionEsther Heid, Kevin P Greenman, Yunsie Chung, et al.
Journal of Chemical Information and Modeling|December 26, 2025
Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property PredictionDavid E Graff, Nathan K Morgan, Jackson W Burns, et al.
Science (New York, N.Y.)|December 21, 2023
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and backBrent A Koscher, Richard B Canty, Matthew A McDonald, et al.
Pageof 1