Title

Physics Inspired Models in Artificial Intelligence

Publication Date

8-2020

Document Type

Conference Proceeding

Abstract

Ideas originating in physics have informed progress in artificial intelligence and machine learning for many decades. However the pedigree of many such ideas is oft neglected in the Computer Science community. The tutorial focuses on current and past ideas from physics that have helped in furthering AI and machine learning. Recent advances in physics inspired ideas in AI are also explored especially how insights from physics may hold the promise of opening the black box of deep learning. Lastly, current and future trends in this area and outlines of a research agenda on how physics-inspired models can benefit AI machine learning is given. © 2020 Owner/Author.

Publication Title

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

First Page

3535

Last Page

3536

DOI

10.1145/3394486.3406464

Open Access Status

Licensed

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