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

Kyle Macaskill

Semi-Parametric Time-Series Models: Computation and Simulation

Matthew Cochran

Low-diameter Networks for Applications on High Performance Computing and Communication Networks

Tiernan Cartwright

The Riemann-Roch Theorem and Dirac Operators

Joshua Borsky

Flexible Microswimmer Geometries in Flow