The goal of Physics \u2229 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.<\/p>\n
10:15 AM\u201311:35 AM
\nShort talks<\/p>\n
Bypassing expensive steps in computational geometry
\nYang-Hui He<\/p>\n
Learning string theory at Large N
\nCody Long<\/p>\n
Training machines to extrapolate reliably over astronomical scales
\nBrent Nelson<\/p>\n
Q&A<\/p>\n
Breaking the tunnel vision with ML
\nSergei Gukov<\/p>\n
Can machine learning give us new theoretical insights in physics and math?
\nWashington Taylor<\/p>\n
Brief overview of machine learning holography
\nYi-Zhuang You<\/p>\n
Q&A<\/p>\n
Applications of persistent homology to physics
\nAlex Cole<\/p>\n
Seeking a connection between the string landscape and particle physics
\nPatrick Vaudrevange<\/p>\n
PBs^-1 to science: novel approaches on real-time processing from LHCb at CERN
\nThemis Bowcock<\/p>\n
Q&A<\/p>\n
From non-parametric to parametric: manifold coordinates with physical meaning
\nMarina Meila<\/p>\n
Machine learning in quantum many-body physics: A blitz
\nYichen Huang<\/p>\n
Knot Machine Learning
\nVishnu Jejjala<\/p>\n
11:35 AM\u201312:30 PM
\nPanel discussion with panelists Michael Freedman, Clement Hongler, Gary Shiu, Paul Smolensky, Washington Taylor<\/p>\n