research note
This paper addresses the challenging inverse problem in chaotic dynamical systems — inferring initial states from given final states
research note
This paper addresses the challenge of early detection of heart murmurs in companion animals, specifically dogs and cats, using smartphone-based auscultation recordings
research note
This paper addresses the stability analysis of Markov Jump Linear Systems (MJLSs), which combine linear dynamical modes switched according to an underlying Markov chain, a model essential in domain…
research note
This paper develops new characterizations and calculus rules for variational convexity, a notion introduced by Rockafellar in 2019 that generalizes classical convexity in a way that guarantees loca…
research note
This dissertation addresses the critical challenge of safely designing and evaluating mental health interventions through virtual simulation to reduce risks inherent in direct real-world experiment…
research note
This paper investigates the potential of Agentic Web Browsers (AWBs), powered by Large Language Models (LLMs), as assistive technologies for visually-impaired users
research note
This paper addresses the challenge of autonomous subsea communication cable inspection using AUVs, where uncertainties in cable route maps, small cable diameters (∼27 mm), partial burial, and envir…
research note
The paper addresses fundamental difficulties in representing cyclic and shared computations purely within the standard λ-calculus, which traditionally requires extensions such as letrec, μ-binders,…
research note
This paper addresses the challenge of applying reinforcement learning (RL) to discrete diffusion Vision-Language-Action (dVLA) models for robotic manipulation
research note
This paper presents Hedgementation, a new benchmark for hedgerow segmentation from remote sensing imagery at country scale with 10m resolution
research note
This paper addresses the computational inefficiency challenge of reference-conditioned image diffusion models, whose runtime and memory costs grow significantly with the number of input reference i…
research note
This paper addresses the challenge of sparse outcome rewards in reinforcement learning (RL), where reward is only given upon task completion, causing difficult credit assignment and slow learning p…
