ML Applied to String Theory and ML Applied to Condensed Matter

Опубликовано 21 мая 2019, 20:05

The goal of Physics ∩ ML is to bring together researchers from machine learning and physics to learn from each other and push research forward together. In this inaugural edition, we will especially highlight some amazing progress made in string theory with machine learning and in the understanding of deep learning from a physical angle. Nevertheless, we invite a cast with wide ranging expertise in order to spark new ideas. Plenary sessions from experts in each field and shorter specialized talks will introduce existing research. We will hold moderated discussions and breakout groups in which participants can identify problems and hopefully begin new collaborations in both directions. For example, physical insights can motivate advanced algorithms in machine learning, and analysis of geometric and topological datasets with machine learning can yield critical new insights in fundamental physics.

11:00 AM-11:45 AM ML applied to string theory | Mike Douglas
11:45 AM-12:30 PM ML applied to condensed matter | Koji Hashimoto

See more at microsoft.com/en-us/research/e...