Physics Inspired Models in Artificial Intelligence
人工智能
深度学习
计算机科学
物理
作者
Muhammad Aurangzeb Ahmad,Şener Özönder
标识
DOI:10.1145/3394486.3406464
摘要
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.