Feynman-Kac measures and Interacting Particle systems :
Selected studies on : Measure valued processes and stochastic partial differential equations
This webpage presents an overview of resources related to the use of particle methods in solving measure valued processes
Branching and Interacting particle approximations
Interacting Markov Chain Monte Carlo Methods
Stochastic models and stability analysis
Feynman-Kac path integrals and semigroups
Probabilistic Interpretations of Schrodinger operators
Kushner-Stratonovitch Equation
This list of topics is clearly far from being exhaustive, and it is partially biased towards my work on stochastic particle models.
More references and links to this subject can be added on demand. This webpage also contains some articles on the mathematical foundations of particle algorithms, and
sequential Monte Carlo methodology. We also recommend to consult the related webpages
The software BIIPS is a general software developed by the INRIA team ALEA
for bayesian inference with interacting particle systems, a.k.a. Sequential Monte Carlo methods.
A demonstration of the BiiPS software for estimating the stochastic volatility of financial data can be found in
Fractional Generalization of Kac Integral(Vasily E. Tarasov, and George M. Zaslavsky; Courant Institute, Skobeltsyn Institute of Nuclear Physics,
Moscow State University, and Department of Physics, New York University 2007)