3 citations · 3 across the 5 of their papers we have counts for
5 papers
Learning Cardiac Electrophysiology Digital Twins Through Agentic Discovery of Hybrid Structure
Ziqi Zhou, Yubo Ye, Sumeet Atul Vadhavka +2
Building personalized cardiac electrophysiology (EP) digital twins requires identifying the appropriate model structure for each patient, not merely fitting parameters. Traditional…
CoMetaPNS: Continually Meta-learning Personalized Neural Surrogates for Cardiac Electrophysiology Simulations
Ryan Missel, Xiajun Jiang, Linwei Wang
Personalized virtual heart simulations face challenges in model personalization and computational cost. While neural surrogates offer state-of-the-art solutions, they typically add…
HyPer-EP: Meta-Learning Hybrid Personalized Models for Cardiac Electrophysiology
Xiajun Jiang, Sumeet Vadhavkar, Yubo Ye +3
Personalized virtual heart models have demonstrated increasing potential for clinical use, although the estimation of their parameters given patient-specific data remain a challeng…
Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework
Yubo Ye, Sumeet Vadhavkar, Xiajun Jiang +3
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series. This presents a significant challenge of identifiability: many…
Hybrid Kinetics Embedding Framework for Dynamic PET Reconstruction
Yubo Ye, Huafeng Liu, Linwei Wang
In dynamic positron emission tomography (PET) reconstruction, the importance of leveraging the temporal dependence of the data has been well appreciated. Current deep-learning solu…