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20122026
most citedA Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

2.7k citations · 4k across the 84 of their papers we have counts for

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2 papers · 1 filter

cs.LG2026★ 33 cited

Bayesian policy gradient and actor-critic algorithms

Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko

Policy gradient methods are reinforcement learning algorithms that adapt a parameterized policy by following a performance gradient estimate. Conventional policy gradient methods u…

cs.LG2026★ 20 cited

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning

Julien Audiffren, Michal Valko, Alessandro Lazaric +1

A popular approach to apprenticeship learning (AL) is to formulate it as an inverse reinforcement learning (IRL) problem. The MaxEnt-IRL algorithm successfully integrates the maxim…