Research Interests
My research lies at the intersection of stochastic processes, statistical inference, and machine learning. I am particularly interested in inference for stochastic differential equations, distribution learning and mixture models, and Bayesian and distributional reinforcement learning, with an emphasis on uncertainty quantification and probabilistic modeling.
Publications and Preprints
Preprints and Submitted Papers
- Learning multiscale stochastic models through normalizing flows. Anan Saha and Arnab Ganguly. Submitted, under review. arXiv:2605.09718
Working Papers
- Neural Reversible-Jump MCMC for Integral-Drift Stochastic Differential Equations. Manuscript in preparation.
- Beyond the Mean: Bayesian Distributional Learning for Risk-Sensitive Offline Contextual Bandits Manuscript in preparation.