2 citations · 4 across the 4 of their papers we have counts for
5 papers
A class of kernel-based scalable algorithms for data science
Philippe G. LeFloch, Jean-Marc Mercier, Shohruh Miryusupov
We present several generative and predictive algorithms based on the RKHS (reproducing kernel Hilbert spaces) methodology, which, most importantly, are scale up efficiently with la…
Extrapolation and generative algorithms for three applications in finance
Philippe G. LeFloch, Jean-Marc Mercier, Shohruh Miryusupov
For three applications of central interest in finance, we demonstrate the relevance of numerical algorithms based on reproducing kernel Hilbert space (RKHS) techniques. Three use c…
Reproducing kernel methods for machine learning, PDEs, and statistics
Philippe G. LeFloch, Jean-Marc Mercier, Shohruh Miryusupov
This monograph develops a unified, application-driven framework for kernel methods grounded in reproducing kernel Hilbert spaces (RKHS) and optimal transport (OT). Part I lays the…
Hamiltonian Flow Simulation of Rare Events
Raphael Douady, Shohruh Miryusupov
Hamiltonian Flow Monte Carlo(HFMC) methods have been implemented in engineering, biology and chemistry. HFMC makes large gradient based steps to rapidly explore the state space. Th…
Optimal Transport Filtering with Particle Reweighing in Finance
Raphael Douady, Shohruh Miryusupov
We show the application of an optimal transportation approach to estimate stochastic volatility process by using the flow that optimally transports the set of particles from the pr…