PhD student, University of Oxford
2 papers at NeurIPS 2025
We propose Permutation Equivariant Graph Neural CDEs, an equivariant and parameter-efficient extension of Graph Neural CDEs for dynamic graph representation learning.
Structured Linear Controlled Differential Equations: A unifying framework for sequence models with structured, input-dependent state-transition matrices
