Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session H71: Poster Session I (2:00pm - 4:00pm)
2:00 PM,
Tuesday, March 16, 2021
Abstract: H71.00176 : A Novel Computational Artificial Intelligence Framework for Complex Physical, Chemical and Biological Networks
Presenter:
Vishnu Shankar
(Institute for Immunity, Transplantation, and Infection, Stanford University)
Authors:
Vishnu Shankar
(Institute for Immunity, Transplantation, and Infection, Stanford University)
Sadasivan Shankar
(Applied Physics, Harvard University)
Our network-based approach encodes reactions in the nodes and the flow of reactants to products in the edges. Our new computing model and highly modular architecture preserves the fundamental physical relationships in reactions and appears to scale more efficiently compared to currently available methods. As this appears to be the first computing model architecture tailored for chemistry and possible extension to biology, we anticipate comparing the performance of our model to current prediction-oriented methods, for which conventional machine learning models are available. The new programming and the information logic of the underlying physics can be used by the community to program different chemical systems as needed for AI systems.
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