Invariant Features for Accurate Predictions of Quantum Chemical UV-vis Spectra of Organic Molecules-Reference-Cited by-同舟云学术

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Invariant Features for Accurate Predictions of Quantum Chemical UV-vis Spectra of Organic Molecules

Published:2024-03-15 Issue: Volume:32 Page:311-320
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Container-title:SoutheastCon 2024
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Author:

Baker Justin¹,Pasini Massimiliano Lupo²,Hauck Cory³

Affiliation:

1. University of Utah,Department of Mathematics,Salt Lake City,Utah,USA

2. Oak Ridge National Laboratory,Computational Sciences and Engineering Division,Oak Ridge,Tennessee,USA

3. Oak Ridge National Laboratory,Computer Science and Mathematics Division,Oak Ridge,Tennessee,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10500015/10500024/10500060.pdf?arnumber=10500060

Reference41 articles.

1. Deep Graph Library: Overview, Updates, and Future Developments [GrAPL 2020 Keynote Speaker]

2. PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models

3. Cormorant: Covariant molecular neural networks;Anderson,2019

4. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

5. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

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