Joel Woodfield

Data-Efficient Reinforcement Learning

This project aims to perform an in-depth study on Schwarzer et al.’s work on Self-Predictive Representations, and develop improved algorithms for data-efficient reinforcement learning.

Joel Woodfield

The University of Queensland

Joel is a third-year bachelor of computer science student majoring in data science at the University of Queensland. He has a strong interest in machine learning, and is currently working on deep reinforcement learning. He is planning to pursue post-graduate study in machine learning in the future. His hobbies include playing music, such as the cornet in a brass band.

You may be interested in

Emmanuel Travassaros

Minimal Spectrahedral Representations for Facial Dimension Realisations

Patrick Gillen

Optimal Insurance Contract from an Principal-Agent Perspective

Bradley Landau

How do phase transitions emerge in discrete vector-spin generalisations of the Curie–Weiss model?

Muhammad Haris Rao

The Representation Theory of Hecke Algebras Through the Knizhnik-Zamolodchikov Functor