7 papers
Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
Larissa Reichart, Cem Ata Baykara, Ali Burak Ãnal +2
Unsupervised multi-source domain adaptation (UMDA) leverages labeled data from multiple source domains to generalize to an unlabeled target. While federated UMDA addresses privacy…
BiTimeCrossNet: Time-Aware Self-Supervised Learning for Pediatric Sleep
Saurav Raj Pandey, Harlin Lee
We present BiTimeCrossNet (BTCNet), a multimodal self-supervised learning framework for long physiological recordings such as overnight sleep studies. While many existing approache…
RELATE: Relation Extraction in Biomedical Abstracts with LLMs and Ontology Constraints
Olawumi Olasunkanmi, Mathew Satusky, Hong Yi +3
Biomedical knowledge graphs (KGs) are vital for drug discovery and clinical decision support but remain incomplete. Large language models (LLMs) excel at extracting biomedical rela…
A Closeness Centrality-based Circuit Partitioner for Quantum Simulations
Doru Thom Popovici, Harlin Lee, Mauro Del Ben +5
Simulating quantum circuits (QC) on high-performance computing (HPC) systems has become an essential method to benchmark algorithms and probe the potential of large-scale quantum c…
Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets
Cem Ata Baykara, Saurav Raj Pandey, Ali Burak Ãnal +2
Developing accurate and generalizable epileptic seizure prediction models from electroencephalography (EEG) data across multiple clinical sites is hindered by patient privacy regul…
Adaptive Multimodal Protein Plug-and-Play with Diffusion-Based Priors
Amartya Banerjee, Xingyu Xu, Caroline Moosmüller +1
In an inverse problem, the goal is to recover an unknown parameter (e.g., an image) that has typically undergone some lossy or noisy transformation during measurement. Recently, de…