John E. Herr

University of Notre Dame — United States

Computer Science · Physical Sciences

9h-index1.5kcitations18works0.02yr avg
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Research Topics

Computational Drug Discovery Methods(15), Machine Learning in Materials Science(15), Protein Structure and Dynamics(5), Various Chemistry Research Topics(4), X-ray Diffraction in Crystallography(2)

Publications18 total

SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials
Scientific Data·2023· 137 citedOpen Access
On the use of real-world datasets for reaction yield prediction
Chemical Science·2023· 120 citedOpen Access
Development of Neural Network Models for Prediction of Molecular Properties
Figshare·2022Open Access
On the Use of Real-World Datasets for Reaction Yield Prediction
2021· 10 citedOpen Access
Graph Neural Networks for Predicting Chemical Reaction Performance
2021· 5 citedOpen Access
Graph Neural Networks for Predicting Chemical Reaction Performance
2021· 5 citedOpen Access
Graph Neural Networks for Predicting Chemical Reaction Performance
2021· 2 citedOpen Access
Few-Shot Graph Learning for Molecular Property Prediction
2021· 142 citedOpen Access
Few-Shot Molecular Property Prediction
The Web Conference·2021
Compressing physics with an autoencoder: Creating an atomic species representation to improve machine learning models in the chemical sciences
The Journal of Chemical Physics·2019· 9 citedOpen Access
Compressing physical properties of atomic species for improving\n predictive chemistry
arXiv (Cornell University)·2018· 29 citedOpen Access
Metadynamics for training neural network model chemistries: A competitive assessment
The Journal of Chemical Physics·2018· 79 citedOpen Access
The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics
Chemical Science·2018· 512 citedOpen Access
The TensorMol-0.1 Model Chemistry: a Neural Network Augmented with Long-Range Physics
arXiv (Cornell University)·2017· 2 citedOpen Access
Origin of the Size-Dependent Stokes Shift in CsPbBr<sub>3</sub> Perovskite Nanocrystals
Journal of the American Chemical Society·2017· 313 citedOpen Access
Intrinsic Bond Energies from a Bonds-in-Molecules Neural Network
The Journal of Physical Chemistry Letters·2017· 135 cited
Bond Energies from a Diatomics-in-Molecules Neural Network
arXiv (Cornell University)·2017Open Access
A Technique for Quantitative Assessment of Three-Dimensional Motion with Applications to Human Joints
Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine·1989· 5 cited

Frequent Co-authors

John Parkhill(8), Kun Yao(7), Olaf Wiest(7), Nitesh V. Chawla(7), Mandana Saebi(5), Bozhao Nan(5), Zhichun Guo(4), David W. Toth(3), Jessica Wahlers(3), Chuxu Zhang(2), Wenhao Yu(2), Meng Jiang(2), Seth N. Brown(2), Jessica Wahlers(2), A. Zuranski(2), Thierry Kogej(2), Per‐Ola Norrby(2), Abigail G. Doyle(2), Ryker Mcintyre(2), Kevin J. Koh(2)