54 citations · 239 across the 57 of their papers we have counts for
70 papers
Forward Reverse Kernel Regression for the Schrödinger bridge problem
Denis Belomestny, John. Schoenmakers
In this paper, we study the Schrödinger Bridge Problem (SBP), which is central to entropic optimal transport. For general reference processes and begin--endpoint distributions, we…
Weighted mesh algorithms for general Markov decision processes: Convergence and tractability
Denis Belomestny, John Schoenmakers
We introduce a mesh-type approach for tackling discrete-time, finite-horizon Markov Decision Processes (MDPs) characterized by state and action spaces that are general, encompassin…
Decompounding Under General Mixing Distributions
Denis Belomestny, Ekaterina Morozova, Vladimir Panov
This study focuses on statistical inference for compound models of the form , where is a random variable denoting the count of summands, which are independent…
Model-free Posterior Sampling via Learning Rate Randomization
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello +6
In this paper, we introduce Randomized Q-learning (RandQL), a novel randomized model-free algorithm for regret minimization in episodic Markov Decision Processes (MDPs). To the bes…
Demonstration-Regularized RL
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello +5
Incorporating expert demonstrations has empirically helped to improve the sample efficiency of reinforcement learning (RL). This paper quantifies theoretically to what extent this…
Nonparametric Bayesian inference for stochastic processes with piecewise constant priors
Denis Belomestny, Frank van der Meulen, Peter Spreij
We present a survey of some of our recent results on Bayesian nonparametric inference for a multitude of stochastic processes. The common feature is that the prior distribution in…