Divya Grover

Visiting Researcher at Data Science and AI

I joined my PhD with Division of Data Science & AI in 2017. My research area is Reinforcement learning, specifically model-based Bayesian Reinforcement learning. I am also TA for Machine learning (TDA231), Discrete Optimization (TDA206) and Introduction to AI (TIN175) courses.

Source: chalmers.se
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Showing 5 publications

2022

Efficient Bayesian Planning

Divya Grover
Doctoral thesis
2022

Minimax-Bayes Reinforcement Learning

Thomas Kleine Buening, Christos Dimitrakakis, Hannes Eriksson et al
Preprint
2020

Bayesian Reinforcement Learning via Deep, Sparse Sampling

Divya Grover, Debabrota Basu, Christos Dimitrakakis
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108. Vol. 108, p. 3036-3044
Paper in proceeding
2020

Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning

Emilio Jorge, Hannes Eriksson, Christos Dimitrakakis et al
Proceedings of Machine Learning Research. Vol. 137, p. 43-52
Paper in proceeding
2020

Sample Efficient Bayesian Reinforcement Learning

Divya Grover
Licentiate thesis

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