An XML-Based Data Model for Moving Object Database. - Xiajun Jiang; Yuping Zhang; Dechang Pi (FGIT-DTA/BSBT, 2010)

基于尺寸建立个性化人体模型的方法 (Personalized Human Body Modeling Method Based on Measurements). - Yidi Gao; Xiajun Jiang; Huibin Shi (计算机科学, 2017)

Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction. - Xiajun Jiang; Sandesh Ghimire; Jwala Dhamala; Zhiyuan Li 007; Prashnna Kumar Gyawali; Linwei Wang (MICCAI (6), 2020)

Deep Adaptive Electrocardiographic Imaging with Generative Forward Model for Error Reduction. - Maryam Toloubidokhti; Prashnna K. Gyawali; Omar A. Gharbia; Xiajun Jiang; Jaume Coll-Font; Jake A. Bergquist; Brian Zenger; Wilson W. Good; Dana H. Brooks; Rob S. MacLeod; Linwei Wang (FIMH, 2021)

Label-Free Physics-Informed Image Sequence Reconstruction with Disentangled Spatial-Temporal Modeling. - Xiajun Jiang; Ryan Missel; Maryam Toloubidokhti; Zhiyuan Li 007; Omar Gharbia; John L. Sapp; Linwei Wang (MICCAI (6), 2021)

Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI. - Xiajun Jiang; Jess D. Tate; Jake Bergquist; Akil Narayan 001; Rob S. MacLeod; Linwei Wang (CinC, 2022)

Few-Shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-learning. - Xiajun Jiang; Zhiyuan Li 007; Ryan Missel; Md Shakil Zaman; Brian Zenger; Wilson W. Good; Rob S. MacLeod; John L. Sapp; Linwei Wang (MICCAI (8), 2022)

Neural State-Space Modeling with Latent Causal-Effect Disentanglement. - Maryam Toloubidokhti; Ryan Missel; Xiajun Jiang; Niels Otani; Linwei Wang (MLMI@MICCAI, 2022)

Learning to Disentangle Inter-Subject Anatomical Variations in Electrocardiographic Data. - Prashnna K. Gyawali; Jaideep Vitthal Murkute; Maryam Toloubidokhti; Xiajun Jiang; B. Milan Horácek; John L. Sapp; Linwei Wang (IEEE Trans. Biomed. Eng., 2022)

Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting. - Xiajun Jiang; Ryan Missel; Zhiyuan Li 007; Linwei Wang (ICLR, 2023)

Continual Unsupervised Disentangling of Self-Organizing Representations. - Zhiyuan Li 007; Xiajun Jiang; Ryan Missel; Prashnna Kumar Gyawali; Nilesh Kumar; Linwei Wang (ICLR, 2023)

A Spatial-Temporally Adaptive PINN Framework for 3D Bi-Ventricular Electrophysiological Simulations and Parameter Inference. - Yubo Ye; Huafeng Liu 003; Xiajun Jiang; Maryam Toloubidokhti; Linwei Wang (MICCAI (7), 2023)

Improving Generalization by Learning Geometry-Dependent and Physics-Based Reconstruction of Image Sequences. - Xiajun Jiang; Maryam Toloubidokhti; Jake Bergquist; Brian Zenger; Wilson W. Good; Rob S. MacLeod; Linwei Wang (IEEE Trans. Medical Imaging, 2023)

DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks. - Maryam Toloubidokhti; Yubo Ye; Ryan Missel; Xiajun Jiang; Nilesh Kumar; Ruby Shrestha; Linwei Wang (ICLR, 2024)

LIBR+: Improving Intraoperative Liver Registration by Learning the Residual of Biomechanics-Based Deformable Registration. - Dingrong Wang; Soheil Azadvar; Jon S. Heiselman; Xiajun Jiang; Michael I. Miga; Linwei Wang (MICCAI (6), 2024)

On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution. - Yubo Ye; Maryam Toloubidokhti; Sumeet Vadhavkar; Xiajun Jiang; Huafeng Liu 003; Linwei Wang (NeurIPS, 2024)

Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework. - Yubo Ye; Sumeet Vadhavkar; Xiajun Jiang; Ryan Missel; Huafeng Liu 003; Linwei Wang (CoRR, 2024)

HyPer-EP: Meta-Learning Hybrid Personalized Models for Cardiac Electrophysiology. - Xiajun Jiang; Sumeet Vadhavkar; Yubo Ye; Maryam Toloubidokhti; Ryan Missel; Linwei Wang (CoRR, 2024)

Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging. - Xiajun Jiang; Ryan Missel; Maryam Toloubidokhti; Karli Gillette; Anton J. Prassl; Gernot Plank; B. Milan Horácek; John L. Sapp; Linwei Wang (IEEE Trans. Medical Imaging, 2024)

Federated Foundation Model for GI Endoscopy Images. - Alina Devkota; Annahita Amireskandari; Joel Palko; Shyam Thakkar; Donald Adjeroh; Xiajun Jiang; Binod Bhattarai; Prashnna K. Gyawali (CoRR, 2025)