29 citations · 103 across the 24 of their papers we have counts for
25 papers
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations
Nilesh Kumar, Ruby Shrestha, Zhiyuan Li +1
Spurious correlation caused by subgroup underrepresentation has received increasing attention as a source of bias that can be perpetuated by deep neural networks (DNNs). Distributi…
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation
Nilesh Kumar, Prashnna K. Gyawali, Sandesh Ghimire +1
Obtaining labelled data in medical image segmentation is challenging due to the need for pixel-level annotations by experts. Recent works have shown that augmenting the object of i…
Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators
Maryam Toloubidokhti, Nilesh Kumar, Zhiyuan Li +5
Prior knowledge about the imaging physics provides a mechanistic forward operator that plays an important role in image reconstruction, although myriad sources of possible errors i…
Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning
Xiajun Jiang, Zhiyuan Li, Ryan Missel +6
Clinical adoption of personalized virtual heart simulations faces challenges in model personalization and expensive computation. While an ideal solution is an efficient neural surr…
Neural State-Space Modeling with Latent Causal-Effect Disentanglement
Maryam Toloubidokhti, Ryan Missel, Xiajun Jiang +2
Despite substantial progress in deep learning approaches to time-series reconstruction, no existing methods are designed to uncover local activities with minute signal strength due…
Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning
Md Shakil Zaman, Jwala Dhamala, Pradeep Bajracharya +5
Probabilistic estimation of cardiac electrophysiological model parameters serves an important step towards model personalization and uncertain quantification. The expensive computa…