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
Ben Cicchini
Investigating the Ecological Diversity-Stability Debate using Differential Equation Models and Statistical Sampling Techniques
Jecinta Jaarola
Improving the Prediction of Patient Outcomes via Integration of Clinical Information with Genome-wide Data
Stephen Dang
Comparison of Regression-Adjusted ABC and Neural Methods for Simulation-Based Inference
