Detailed Balanced Chemical Reaction Networks as Generalized Boltzmann Machines

Explore the intersection of chemical reaction networks and machine learning in this comprehensive lecture. Delve into the concept of detailed balanced chemical reaction networks and their relationship to generalized Boltzmann machines. Examine key topics including machine learning fundamentals, Boltzmann machines, biology motivations, and the Product Poisson Theorem. Investigate complex distributions, hidden units, energy clamping, and in silico examples. Learn about autonomous learning techniques, thermodynamics applications, and the implications of breaking detailed balance. Gain insights into this interdisciplinary field through a structured presentation followed by a Q&A session.

Introduction
What is Machine Learning
Boltzmann Machines
Biology
Motivation
Detailed balanced crns
Product Poisson Theorem
Complex Distributions
Product Poisson Distribution
In silico
Hidden units
Energy clamping
Examples
Learning
Clamping
Breaking detail balanced
General autonomous learning
Thermodynamics
Summary
Questions