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Kevin P. Greenman
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Chemprop: A machine learning package for chemical property prediction
E Heid, KP Greenman, Y Chung, SC Li, DE Graff, FH Vermeire, H Wu, ...
Journal of Chemical Information and Modeling 64 (1), 9-17, 2023
462023
Learning matter: Materials design with machine learning and atomistic simulations
S Axelrod, D Schwalbe-Koda, S Mohapatra, J Damewood, KP Greenman, ...
Accounts of Materials Research 3 (3), 343-357, 2022
452022
Multi-fidelity prediction of molecular optical peaks with deep learning
KP Greenman, WH Green, R Gómez-Bombarelli
Chemical Science, 2022
322022
Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back
BA Koscher, RB Canty, MA McDonald, KP Greenman, CJ McGill, ...
Science 382 (6677), eadi1407, 2023
162023
Benchmarking uncertainty quantification for protein engineering
KP Greenman, AP Amini, KK Yang
bioRxiv, 2023.04. 17.536962, 2023
82023
Lattice-constant and band-gap tuning in wurtzite and zincblende BInGaN alloys
K Greenman, L Williams, E Kioupakis
Journal of Applied Physics 126 (5), 055702, 2019
82019
Automated patent extraction powers generative modeling in focused chemical spaces
A Subramanian, KP Greenman, A Gervaix, T Yang, R Gómez-Bombarelli
Digital Discovery 2 (4), 1006-1015, 2023
42023
An Undergraduate-Led, Research-Based Course That Complements a Traditional Chemical Engineering Curriculum
S Butrus, K Greenman, E Khera, I Kopyeva, A Nishii
Chemical Engineering Education 54 (2), 97-106, 2020
12020
Multi-Fidelity Deep Learning for Data-Efficient Molecular Property Models from Experimental and Computational Data
KP Greenman, T Orkhon, W Green, R Gomez-Bombarelli
2023 AIChE Annual Meeting, 2023
2023
Multi-Fidelity Computer-Aided Molecular Design
KP Greenman
2023 AIChE Annual Meeting, 2023
2023
Chemprop: Machine Learning for Molecular Property Prediction
C McGill, E Heid, Y Chung, K Greenman, D Graff, M Liu, C Bilodeau, ...
2022 AIChE Annual Meeting, 2022
2022
Design of an Automatic Platform for Machine-Learning Model Based Molecular Property Optimization
M McDonald, B Koscher, R Canty, SK Ha, C Bilodeau, KP Greenman, ...
2022 AIChE Annual Meeting, 2022
2022
MULTI-FIDELITY DEEP LEARNING AND ACTIVE LEARNING FOR MOLECULAR OPTICAL PROPERTIES
KP Greenman
International Symposium on Molecular Spectroscopy, 2022
2022
Transfer Learning for Prediction of Absorption and Emission Spectra from Multi-Fidelity Data
KP Greenman, W Green, R Gomez-Bombarelli
2021 AIChE Annual Meeting, 2021
2021
Designing and Synthesizing Novel Dye Molecules Using Generative Modeling and Data-Driven Synthesis Planning
C Bilodeau, B Koscher, KP Greenman, R Gómez-Bombarelli, KF Jensen
2021 AIChE Annual Meeting, 2021
2021
Lattice Constant and Band Gap Tuning in BInGaN Alloys for Next-Generation LEDs
K Greenman, L Williams, E Kioupakis
APS Meeting Abstracts, 2019
2019
Computational Catalysis: Creating a User-Friendly Tool for Research and Education
KP Greenman, P Liao
2018 AIChE Annual Meeting, 2018
2018
Computational Catalysis with DFT
K Greenman, P Liao
nanoHUB, 2018
2018
BInGaN alloys lattice-matched to GaN for high-power high-efficiency visible LEDs
L Williams, K Greenman, E Kioupakis
APS Meeting Abstracts, 2018
2018
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