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08/12/2023
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations
Spurious correlation caused by subgroup underrepresentation has received...
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07/25/2023
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation
Obtaining labelled data in medical image segmentation is challenging due...
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11/02/2022
Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators
Prior knowledge about the imaging physics provides a mechanistic forward...
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10/06/2022
Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning
Clinical adoption of personalized virtual heart simulations faces challe...
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09/26/2022
Neural State-Space Modeling with Latent Causal-Effect Disentanglement
Despite substantial progress in deep learning approaches to time-series ...
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10/13/2021
Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning
Probabilistic estimation of cardiac electrophysiological model parameter...
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03/17/2021
Semi-Supervised Learning for Eye Image Segmentation
Recent advances in appearance-based models have shown improved eye track...
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09/23/2020
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization
The success of deep learning relies on the availability of large-scale a...
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07/18/2020
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction
Deep neural networks have shown great potential in image reconstruction ...
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06/02/2020
Quantifying the Uncertainty in Model Parameters Using Gaussian Process-Based Markov Chain Monte Carlo: An Application to Cardiac Electrophysiological Models
Estimation of patient-specific model parameters is important for persona...
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05/22/2020
Semi-supervised Medical Image Classification with Global Latent Mixing
Computer-aided diagnosis via deep learning relies on large-scale annotat...
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05/15/2020
High-dimensional Bayesian Optimization of Personalized Cardiac Model Parameters via an Embedded Generative Model
The estimation of patient-specific tissue properties in the form of mode...
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02/25/2020
Reliable Estimation of Kullback-Leibler Divergence by Controlling Discriminator Complexity in the Reproducing Kernel Hilbert Space
Several scalable methods to compute the Kullback Leibler (KL) divergence...
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02/24/2020
Progressive Learning and Disentanglement of Hierarchical Representations
Learning rich representation from data is an important task for deep gen...
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09/03/2019
Improving Disentangled Representation Learning with the Beta Bernoulli Process
To improve the ability of VAE to disentangle in the latent space, existi...
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07/22/2019
Semi-Supervised Learning by Disentangling and Self-Ensembling Over Stochastic Latent Space
The success of deep learning in medical imaging is mostly achieved at th...
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07/01/2019
Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization
Personalization of cardiac models involves the optimization of organ tis...
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05/12/2019
Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential
Noninvasive reconstruction of cardiac transmembrane potential (TMP) from...
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03/05/2019
Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences
Deep learning networks have shown state-of-the-art performance in many i...
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10/31/2018
Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factors
While deep representation learning has become increasingly capable of se...
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10/12/2018
Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential
Deep learning models have shown state-of-the-art performance in many inv...
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08/04/2018