activity
20162024
most citedA boundary theory approach to de Finetti's theorem

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ML2024

On Policy Evaluation Algorithms in Distributional Reinforcement Learning

Julian Gerstenberg, Ralph Neininger, Denis Spiegel

We introduce a novel class of algorithms to efficiently approximate the unknown return distributions in policy evaluation problems from distributional reinforcement learning (DRL).…

math.PR2022

Exchangeable Laws in Borel Data Structures

Julian Gerstenberg

Motivated by statistical practice, category theory terminology is used to introduce Borel data structures and study exchangeability in an abstract framework. A generalization of de…

stat.ML2022

On solutions of the distributional Bellman equation

Julian Gerstenberg, Ralph Neininger, Denis Spiegel

In distributional reinforcement learning not only expected returns but the complete return distributions of a policy are taken into account. The return distribution for a fixed pol…

math.PR2018

Exchangeable interval hypergraphs and limits of ordered discrete structures

Julian Gerstenberg

A hypergraph is called an interval hypergraph if there exists a linear order on such that every edge is an interval w.r.t. ; we also assume that $\{j\}\…

math.PR2017

General Erased-Word Processes: Product-Type Filtrations, Ergodic Laws and Martin Boundaries

Julian Gerstenberg

We study the dynamics of erasing randomly chosen letters from words by introducing a certain class of discrete-time stochastic processes, general erased-word processes(GEWPs), and…

math.PR2016★ 1 cited

A boundary theory approach to de Finetti's theorem

Julian Gerstenberg, Rudolf Grübel, Klaas Hagemann

We show that boundary theory for transient Markov chains, as initiated by Doob, can be used to prove de Finetti's classical representation result for exchangeable random sequences.…