works on

From the 1 of 15 linked papers with an AI index.

activity
20242026
collaborators

15 papers

cs.LG2026

RTS Smoother-Guided Learning of Physics-Based Neural Differential Models

Ahmet Demirkaya, Georgios Stratis, Tales Imbiriba +2

The paper introduces a hybrid neural‑physics framework that combines known ODE components with neural networks to learn missing dynamics, using a Rauch‑Tung‑Striebel smoother for l…

stat.AP2026

Temporal Point Process Modeling of Aggressive Behavior Onset in Psychiatric Inpatient Youths with Autism

Michael Potter, Michael Everett, Ashutosh Singh +6

Aggressive behavior, including aggression towards others and self-injury, occurs in up to 80% of children and adolescents with autism, making it a leading cause of behavioral healt…

cs.CV2025

SSplain: Sparse and Smooth Explainer for Retinopathy of Prematurity Classification

Elifnur Sunger, Tales Imbiriba, Peter Campbell +3

Neural networks are frequently used in medical diagnosis. However, due to their black-box nature, model explainers are used to help clinicians understand better and trust model out…

eess.IV2025

Tubular Curvature Filter: Pointwise Curvature Calculation for Tubular Objects in Images

Elifnur Sunger, Beyza Kalkanli, Veysi Yildiz +4

Purpose: Accurate estimation of blood vessel tortuosity from medical images is an extremely important and challenging task. It is particularly relevant in the context of retinopath…

eess.SP2025

Trends and Challenges in Next-Generation GNSS Interference Management

Leatile Marata, Mariona Jaramillo-Civill, Tales Imbiriba +4

The global navigation satellite system (GNSS) continues to evolve in order to meet the demands of emerging applications such as autonomous driving and smart environmental monitorin…

cs.LG2025

Bayesian Jammer Localization with a Hybrid CNN and Path-Loss Mixture of Experts

Mariona Jaramillo-Civill, Luis González-Gudiño, Tales Imbiriba +1

Global Navigation Satellite System (GNSS) signals are vulnerable to jamming, particularly in urban areas where multipath and shadowing distort received power. Previous data-driven…