I am a PhD student in Mathematics at Imperial College London supervised by Andrew Duncan and Greg Pavliotis.

Summary

My research focuses on developing and analysing robust methodologies for unsupervised machine learning based on techniques from physics, mathematical analysis, and optimisation. Currently, I am working on an improved training methodology for energy-based models for generative modelling and inference.

Publications

• Deep Optimal Sensor Placement for Black Box Stochastic Simulations
  Paula Cordero-Encinar, Tobias Schröder, Peter Yatsyshin, Andrew Duncan. AISTATS 2025
• Training Discrete Energy-Based Models with Energy Discrepancy
  Tobias Schröder, Zijing Ou, Yingzhen Li, Andrew B. Duncan. NeurIPS 2024
• Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  Tobias Schröder, Zijing Ou, Jen Ning Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew B. Duncan. NeurIPS 2023