3 papers
cs.IT2026
Importance Sampling for Event Discovery via Guesswork
Asaf Cohen
Traditional importance sampling (IS) is designed to estimate rare-event probabilities by minimizing estimator variance. However, many applications prioritize rapid discovery: the g…
math.OC2026
Operator Learning for Families of Finite-State Mean-Field Games
William Hofgard, Asaf Cohen, Mathieu Laurière
Finite-state mean-field games (MFGs) arise as limits of large interacting particle systems and are governed by an MFG system, a coupled forward-backward differential equation consi…
math.PR2025
Uniform-in-Time Convergence Rates to a Nonlinear Markov Chain for Mean-Field Interacting Jump Processes
Asaf Cohen, Ethan Huffman
We consider a system of particles interacting through their empirical distribution on a finite state space in continuous time. In the formal limit as , the system t…