John E. Herr - Concepedia

Concepedia

Author

John E. Herr

University of Notre Dame ORCID

Also Known As

Herr, John, Herr, John E., J E Herr, John E. Herr, John Herr

18

Publications

1.5K

Citations

9

H-Index

28

Concepts

All Affiliations

University of Notre Dame Princeton University AstraZeneca (Sweden)

JE

About

John E. Herr is an author at University of Notre Dame specializing in engineering, data science, and machine learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	3	3	395
2	Data Science	3	3	395
3	Chemistry	2	2	254
4	Medicine	1	1	141
5	Natural Sciences	1	1	135

John E. Herr

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9

Publications

1.5K

Citations

9

H-Index

	Year	Citations
The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics Kun Yao, John E. Herr, David W. Toth, Chemical Science	2018	512
Origin of the Size-Dependent Stokes Shift in CsPbBr<sub>3</sub> Perovskite Nanocrystals Michael C. Brennan, John E. Herr, Triet S. Nguyen-Beck, Journal of the American Chemical Society	2017	313
Few-Shot Graph Learning for Molecular Property Prediction Zhichun Guo, Chuxu Zhang, Wenhao Yu, Few-shot LearningGeometric LearningEngineeringMachine LearningMolecular Biology	2021	141
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter Eastman, Pavan Kumar Behara, David Dotson, Scientific Data	2023	137
Intrinsic Bond Energies from a Bonds-in-Molecules Neural Network Kun Yao, John E. Herr, Seth N. Brown, The Journal of Physical Chemistry Letters EngineeringIntrinsic Bond EnergiesData SciencePhysic Aware Machine LearningNatural Sciences	2017	135
On the use of real-world datasets for reaction yield prediction Mandana Saebi, Bozhao Nan, John E. Herr, Chemical Science Artificial IntelligenceEngineeringMachine LearningEln DatasetMachine Learning Tool	2023	119
Metadynamics for training neural network model chemistries: A competitive assessment John E. Herr, Kun Yao, Ryker Mcintyre, The Journal of Chemical Physics	2018	79
Compressing physical properties of atomic species for improving\n predictive chemistry John E. Herr, Kevin J. Koh, Kun Yao, arXiv (Cornell University)	2018	29
On the Use of Real-World Datasets for Reaction Yield Prediction Mandana Saebi, Bozhao Nan, John E. Herr,	2021	10

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