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LIBR+: Improving Intraoperative Liver Registration by Learning the Residual of Biomechanics-Based Deformable Registration.

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Improving Disentangled Representation Learning with the Beta Bernoulli Process., , , , , , and . ICDM, page 1078-1083. IEEE, (2019)Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework., , , , , and . CoRR, (2024)Noninvasive Computational Imaging of Cardiac Electrophysiology for 3-D Infarct., , , , and . IEEE Trans. Biomed. Eng., 58 (4): 1033-1043 (2011)Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential., , , , , and . CoRR, (2019)Spatially Adaptive Multi-Scale Optimization for Local Parameter Estimation in Cardiac Electrophysiology., , , , , , and . IEEE Trans. Med. Imaging, 36 (9): 1966-1978 (2017)L_0 Norm Based Sparse Regularization for Non-invasive Infarct Detection Using ECG Signal., and . CinC, www.cinc.org, (2017)Deep Learning Aided Time-Frequency Analysis Filter Framework for Suppressing Ionosphere Clutter., , , , , and . Remote. Sens., 14 (14): 3424 (2022)Learning Disentangled Representation from 12-Lead Electrograms: Application in Localizing the Origin of Ventricular Tachycardia., , , and . AAAI Workshops, volume WS-18 of AAAI Technical Report, page 443-450. AAAI Press, (2018)A Common-Ground Review of the Potential for Machine Learning Approaches in Electrocardiographic Imaging Based on Probabilistic Graphical Models., , and . CinC, page 1-4. www.cinc.org, (2018)Overcoming Barriers to Quantification and Comparison of Electrocardiographic Imaging Methods: a Community-Based Approach., , , , , , , and . CinC, www.cinc.org, (2017)