Mark Rowland

Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

A distributional code for value in dopamine-based reinforcement learning

Discovering faster matrix multiplication algorithms with reinforcement learning

An Introduction to Variational Autoencoders

Reconfigurable Intelligent Surfaces: Principles and Opportunities

Rényi divergence variational inference

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications

Review on deep learning applications in frequency analysis and control of modern power system

Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions

Deep Reinforcement Learning: A Survey

A survey and critique of multiagent deep reinforcement learning

Top-down design of protein architectures with reinforcement learning

α-Rank: Multi-Agent Evaluation by Evolution

Distributional Reinforcement Learning With Quantile Regression

Statistics and Samples in Distributional Reinforcement Learning

Distributional Reinforcement Learning with Quantile Regression

Black-Box α-divergence minimization