A mix of introductory lectures and research talks on partition functions and techniques for their computation, including methods such as Markov chains, correlation decay, belief propagation and convex optimization.
The main goal of this workshop would be to introduce the techniques to estimate or compute to compute partition functions in the following areas to a broad mathematical audience. The workshop will also have regular open discussion sessions.
- Markov Chain Monte Carlo methods
- Belief Propagation and Bethe Approximation methods
- Scaling, analytical, polynomial-based methods
- Correlation decay methods
- Graph lifts based approach to estimate partition functions
- Real-stable polynomials and bounds on partition functions
- Entropy-based/convex optimization approach
- Alexander Barvinok
- Michael Chertkov
- Peter Csikvari
- Leonid Gurvits
- Alex Samorodnitsky
- Mohit Singh
- Piyush Srivastava
- Daniel Stefankovic
- Eric Vigoda
- Pascal Vontobel
- Yitong Yin