3 papers
physics.data-an2026
Maximum Likelihood Particle Tracking in Turbulent Flows via Sparse Optimization
Griffin M Kearney, Kasey M Laurent, Makan Fardad
Lagrangian particle tracking is essential for characterizing turbulent flows, but inferring particle acceleration from inherently noisy position data remains a significant challeng…
cs.LG2026
Kinematic Tokenization: Optimization-Based Continuous-Time Tokens for Learnable Decision Policies in Noisy Time Series
Griffin Kearney
Transformers are designed for discrete tokens, yet many real-world signals are continuous processes observed through noisy sampling. Discrete tokenizations (raw values, patches, fi…
math.OC2025
Adaptive Clutter Suppression via Convex Optimization
Yifan He, Griffin Kearney, Makan Fardad
Passive and bistatic radar systems are often limited by strong clutter and direct-path interference that mask weak moving targets. Conventional cancellation methods such as the ext…