29 citations · 80 across the 24 of their papers we have counts for
6 papers · 1 filter
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization
Prashnna Kumar Gyawali, Sandesh Ghimire, Linwei Wang
The success of deep learning relies on the availability of large-scale annotated data sets, the acquisition of which can be costly, requiring expert domain knowledge. Semi-supervis…
Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets
Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu +2
Chest radiography is the most common medical image examination for screening and diagnosis in hospitals. Automatic interpretation of chest X-rays at the level of an entry-level rad…
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction
Xiajun Jiang, Sandesh Ghimire, Jwala Dhamala +3
Deep neural networks have shown great potential in image reconstruction problems in Euclidean space. However, many reconstruction problems involve imaging physics that are dependen…
Semi-supervised Medical Image Classification with Global Latent Mixing
Prashnna Kumar Gyawali, Sandesh Ghimire, Pradeep Bajracharya +2
Computer-aided diagnosis via deep learning relies on large-scale annotated data sets, which can be costly when involving expert knowledge. Semi-supervised learning (SSL) mitigates…
High-dimensional Bayesian Optimization of Personalized Cardiac Model Parameters via an Embedded Generative Model
Jwala Dhamala, Sandesh Ghimire, John L. Sapp +2
The estimation of patient-specific tissue properties in the form of model parameters is important for personalized physiological models. However, these tissue properties are spatia…
Analysis of Discriminator in RKHS Function Space for Kullback-Leibler Divergence Estimation
Sandesh Ghimire, Prashnna K Gyawali, Linwei Wang
Several scalable sample-based methods to compute the Kullback Leibler (KL) divergence between two distributions have been proposed and applied in large-scale machine learning model…