1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2025
Dynamical Implicit Neural Representations
Yesom Park, Kelvin Kan, Thomas Flynn +4
Implicit Neural Representations (INRs) provide a powerful continuous framework for modeling complex visual and geometric signals, but spectral bias remains a fundamental challenge,…
cs.LG2025
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
Kelvin Kan, Xingjian Li, Benjamin J. Zhang +3
We study Transformers through the perspective of optimal control theory, using tools from continuous-time formulations to derive actionable insights into training and architecture…
cs.LG2025★ 1 cited
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization
Kelvin Kan, Xingjian Li, Stanley Osher
Transformers have achieved state-of-the-art performance in numerous tasks. In this paper, we propose a continuous-time formulation of transformers. Specifically, we consider a dyna…