Full Professor, The University of Warwick
3 papers at NeurIPS 2025
We propose Interactive Retrosynthesis Planning, a novel framework that learns to construct retrosynthetic routes by interacting with tree MDPs and optimising a worst-path objective by self-imitation learning.
A verified unlearning method provides an efficient mechanism to update models when either the student's or the teacher's data receive unlearning requests.
