Preprint
Jul 2026
Advances in Neural Controlled Differential Equations
This thesis advances the training and scalability of NCDEs through three complementary contributions, building on neural rough differential equations, which reduce the time per training step for an NCDE by up to three orders of magnitude while achieving state-of-the-art performance across diverse time series benchmarks.
Benjamin Walker
· 1 citation