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
Recommended Citation
Ahmad, M. A., & Özönder, A. (2020). Physics Inspired Models in Artificial Intelligence. 3535–3536. Scopus. https://doi.org/10.1145/3394486.3406464