Paul L. Houston
American chemist
Facts
10 properties- Instance of
- human
- Date of birth
- 1947
- Country of citizenship
- United States[5]
- Occupation
- physical chemist, researcher, professor
- Educated at
- Yale University, Massachusetts Institute of Technology, University of California, Berkeley, Massachusetts Institute of Technology, Yale University[8][9][10]
🏷️ Also known as
en Paul L Houston
🔖 Identifiers · 12
- ISNI
- 0000000117123048
- ORCID iD
- 0000-0003-2566-9539
- VIAF cluster ID
- 163078982
- GND ID
- 1020321601
- Academic Tree ID
- 63522
- Awards & Winners artist ID
- 04y73h8
- Freebase ID
- /m/04y73h8
- Guggenheim fellows ID
- paul-l-houston
- NL CR AUT ID
- ctu2011675707
- NUKAT ID
- n2005137007
- SHARE Catalogue author ID
- 607175
- Yale LUX ID
- person/4e11d35e-2fa9-4c19-ac66-3ddb93f3cee9
🔗 Connections
Author of 6
A Machine Learning Approach for Prediction of Rate Constants,
A Machine Learning Approach for Rate Constants. II. Clustering, Training, and Predictions for the O(<sup>3</sup>P) + HCl → OH + Cl Reaction,
A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential,
Permutationally invariant polynomial regression for energies and gradients, using reverse differentiation, achieves orders of magnitude speed-up with high precision compared to other machine learning methods,
The MD17 datasets from the perspective of datasets for gas-phase “small” molecule potentials,
Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(<i>T</i>) Level Illustrated for Ethanol
← Authored by 6
A Machine Learning Approach for Prediction of Rate Constants,
A Machine Learning Approach for Rate Constants. II. Clustering, Training, and Predictions for the O(<sup>3</sup>P) + HCl → OH + Cl Reaction,
A Δ-machine learning approach for force fields, illustrated by a CCSD(T) 4-body correction to the MB-pol water potential,
Permutationally invariant polynomial regression for energies and gradients, using reverse differentiation, achieves orders of magnitude speed-up with high precision compared to other machine learning methods,
The MD17 datasets from the perspective of datasets for gas-phase “small” molecule potentials,
Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(<i>T</i>) Level Illustrated for Ethanol
Affiliated with 4
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Summary
Paul L. Houston was born on 1947[1]. He has worked as a physical chemist[2], researcher[3], and professor[4].
FAQs
What did Paul L. Houston do for work?
Paul L. Houston worked as a physical chemist[2], researcher[3], and professor[4].
Where did Paul L. Houston go to school?
Paul L. Houston was educated at Yale University[8], Massachusetts Institute of Technology[9], and University of California, Berkeley[10].
What awards did Paul L. Houston receive?
Honors received include Guggenheim Fellowship[11], Herbert P. Broida Prize[12], and Fellow of the American Association for the Advancement of Science[13].