Machine Learning, Statistical Physics, and Ecological Dynamics

 · Invited

Abstract

In this talk, I will start by giving an overview of Machine Learning from a physics perspective and highlight open problems where physicists can contribute. I will then discuss the many connections between the statistical physics of disordered systems and ML. Building on this discussion, I will argue that, somewhat suprisingly, ML is also intimately related to ecological dynamics. I will show how many ML methods and concepts have natural counterparts and ecology and argue that these fields can and should cross-fertalize each other.

*The work was supported by NIH NIGMS grant 1R35GM119461, Simons Investigator in the Mathematical Modeling of Living Systems (MMLS) to PM, and the Scialog Program sponsored jointly by Research Corporation for Science Advancement (RCSA) and the Gordon and Betty Moore Foundation.

Presenters

  • Pankaj Mehta

    • Boston University
    • Physics, Boston University
    • Department of Physics, Boston University

Authors

  • Pankaj Mehta

    • Boston University
    • Physics, Boston University
    • Department of Physics, Boston University