14 papers
Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy
Thi Kieu Khanh Ho, Thomas Lai, Petr Klimes +5
Accurate identification of the epileptogenic zone (EZ) is essential for seizure freedom after resective surgery in drug-resistant epilepsy, yet seizure freedom rates remain below 5…
Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying
Abhijeet Praveen, Sareh Soleimani, Cormac Cureton +4
Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quality. However, these particle…
Unsupervised Continual Clustering via Forward-Backward Knowledge Distillation
Mohammadreza Sadeghi, Sareh Soleimani, Zihan Wang +1
Unsupervised Continual Learning (UCL) aims to enable neural networks to learn sequential tasks without labels or access to past data. A major challenge in this setting is Catastrop…
TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data
Cormac Cureton, Narges Armanfard
Prior-Data Fitted networks (PFNs) have been very successful in tabular contexts, handling prediction tasks in context. However, they are designed for single-task inference, meaning…
ARTA: Adversarial-Robust Multivariate Time--Series Anomaly Detection via Sparsity-Constrained Perturbations
Hadi Hojjati, Narges Armanfard
Time-series anomaly detection (TSAD) is a critical component in monitoring complex systems, yet modern deep learning-based detectors are often highly sensitive to localized input c…
EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset
Hadi Hojjati, Christopher Roth, Rory Woods +2
The progress of Anomaly Detection (AD) in safety-critical domains, such as transportation, is severely constrained by the lack of large-scale, real-world benchmarks. To address thi…