Co-authors: Xavier Merino (Florida Institute of Technology), Ashutosh Sonar (Florida Institute of Technology), Nezamoddin N Kachouie (Florida Institute of Technology-Department of Mathematical Sciences)

Medical imaging repositories metadata integration cloud-native data infrastructure reproducible research AI-assisted data discovery scalable analytics

Maximum Likelihood Estimation for Entity Ranking under Iterative Synthetic Data Augmentation

4:50 PM - 5:05 PM

Yiqiao Jin (Washington University in St. Louis)

Co-authors: Mengxin Yu

Model collapse Entity ranking Uncertainty quantification Iterative maximum likelihood estimator

Statistical Inference for Subgraph Frequencies of Exchangeable Hyperedge Models

5:05 PM - 5:20 PM

Ayoushman Bhattacharya (Washington University in St. Louis)

Co-authors: Nilanjan Chakraborty (Missouri University of Science and Technology), Robert Lunde

Network data analysis Higher-order interactions Hypergraphs Network motifs Uncertainty quantification

The Learnable Delta Method: Bridging Classical Error Propagation and Deep Learning Optimization

5:20 PM - 5:35 PM

Pei-Hsuan Hsia

Co-authors: Lars H. Heyen (Scientific Computing Center, Karlsruhe Institute of Technology), Arvid Weyrauch (Scientific Computing Center, Karlsruhe Institute of Technology), Markus Goetz (Scientific Computing Center, Karlsruhe Institute of Technology), Achim Streit (Scientific Computing Center, Karlsruhe Institute of Technology), Sebastian Krumscheid (Scientific Computing Center, Karlsruhe Institute of Technology), Charlotte Debus (Scientific Computing Center, Karlsruhe Institute of Technology)

uncertainty quantification uncertainty propagation error propagation neural networks delta method

Uncertainty-Aware Deep Learning for High-Confidence Prediction in Diabetic Retinopathy Imaging

5:35 PM - 5:50 PM

GM Fahad Bin Mostafa (Arizona State University)

Co-authors: Hafiz Khan (Texas Tech Health Sciences Center)

Diabetic Retinopathy Uncertainty Quantification Bayesian Deep Learning Spatial Feature Modeling Clinical AI Reliability