PhD student in probabilistic machine learning
Queen Mary University | Oxford-Man Institute
# About
PhD student in Bayesian machine learning. I’m interested in the intersection between machine learning and statistics, with a focus on online learning, Bayesian inference, and neural networks. I work on developing efficient online learning algorithms for neural networks, with applications to bandits and streaming data.
# PhD supervisors
# Research
- Detecting toxic flow — Cartea A., Duran-Martin, G., & Sánchez-Betancourt, L. @ arXiv 2023 (preprint)
- Low-rank extended Kalman filtering for online learning of neural networks from streaming data — Chang, P.G., Duran-Martin, G., Shestopaloff, A., Jones, M. & Murphy, K.P. @ CoLLAs 2023
- Efficient online Bayesian inference for neural bandits — Duran-Martin, G., Kara, A. & Murphy, K. @ AiStats 2022
# Talks
- Detecting toxic flow — November 2023, Oxford-Man institute
- Online training of Bayesian neural networks — November 2023, stats students’s seminar, University of Edinburgh (online)
- https://gerdm.github.io/qmul-fire-talk-0323 — PhD fire talks 2023, Queen Mary University
- Subspace neural bandits — AiStats 2021 (online)