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ORCIDSandesh Ghimire
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2020 – today
- 2024
[c23]Davin Hill, Aria Masoomi, Max Torop, Sandesh Ghimire, Jennifer G. Dy:
Boundary-Aware Uncertainty for Feature Attribution Explainers. AISTATS 2024: 55-63- [c22]Jinyang Liu, Wondmgezahu Teshome, Sandesh Ghimire, Mario Sznaier, Octavia I. Camps:
Solving Masked Jigsaw Puzzles with Diffusion Vision Transformers. CVPR 2024: 23009-23018 - [i22]Jinyang Liu, Wondmgezahu Teshome, Sandesh Ghimire, Mario Sznaier, Octavia I. Camps:
Solving Masked Jigsaw Puzzles with Diffusion Vision Transformers. CoRR abs/2404.07292 (2024) - 2023
- [j2]Krishna Mridha
, Sandesh Ghimire, Jungpil Shin, Anmol Aran, Md. Mezbah Uddin, Muhammad Firoz Mridha:
Automated Stroke Prediction Using Machine Learning: An Explainable and Exploratory Study With a Web Application for Early Intervention. IEEE Access 11: 52288-52308 (2023) - [c21]Armand Comas Massague, Yilun Du, Christian Fernandez Lopez, Sandesh Ghimire, Mario Sznaier, Joshua B. Tenenbaum, Octavia I. Camps:
Inferring Relational Potentials in Interacting Systems. ICML 2023: 6364-6383 - [c20]Sandesh Ghimire, Shinsaku Kataoka, Lillian Pentecost:
NVMSurvey: Recent Advances and Comparative Analysis of Emerging Non-Volatile Memories (eNVMs). IISWC 2023: 229-231 - [c19]Armand Comas Massague, Christian Fernandez Lopez, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia I. Camps:
Learning Object-Centric Dynamic Modes from Video and Emerging Properties. L4DC 2023: 745-769 - [c18]Nilesh Kumar, Prashnna K. Gyawali, Sandesh Ghimire, Linwei Wang:
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation. MICCAI (2) 2023: 255-265 - [c17]Krishna Mridha, Fitsum Getachew Tola, Shakil Sarkar, Nazmul Arefin, Sandesh Ghimire, Anmol Aran, Aashish Prashad Pandey:
Automating Malaria Diagnosis with XAI: Using Deep-Learning Technologies for More Accurate, Efficient, and Transparent Results. MIWAI 2023: 297-308 - [i21]Sandesh Ghimire, Armand Comas Massague, Davin Hill, Aria Masoomi, Octavia I. Camps, Jennifer G. Dy:
Divide and Compose with Score Based Generative Models. CoRR abs/2302.02272 (2023) - [i20]Sandesh Ghimire, Jinyang Liu, Armand Comas Massague, Davin Hill, Aria Masoomi, Octavia I. Camps, Jennifer G. Dy:
Geometry of Score Based Generative Models. CoRR abs/2302.04411 (2023) - [i19]Nilesh Kumar, Prashnna K. Gyawali, Sandesh Ghimire, Linwei Wang:
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation. CoRR abs/2307.13645 (2023) - [i18]Armand Comas Massague, Yilun Du, Christian Fernandez Lopez, Sandesh Ghimire, Mario Sznaier, Joshua B. Tenenbaum, Octavia I. Camps:
Inferring Relational Potentials in Interacting Systems. CoRR abs/2310.14466 (2023) - 2022
- [i17]Davin Hill, Aria Masoomi, Sandesh Ghimire, Max Torop, Jennifer G. Dy:
Explanation Uncertainty with Decision Boundary Awareness. CoRR abs/2210.02419 (2022) - 2021
- [c16]Sandesh Ghimire, Aria Masoomi, Jennifer G. Dy:
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space. NeurIPS 2021: 10221-10233 - [i16]Sandesh Ghimire, Aria Masoomi, Jennifer G. Dy:
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space. CoRR abs/2109.14688 (2021) - [i15]Armand Comas Massague, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia I. Camps:
Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective. CoRR abs/2110.00547 (2021) - [i14]Max Torop, Sandesh Ghimire, WenQian Liu, Dana H. Brooks, Octavia I. Camps, Milind Rajadhyaksha, Jennifer G. Dy, Kivanç Köse:
Unsupervised Approaches for Out-Of-Distribution Dermoscopic Lesion Detection. CoRR abs/2111.04807 (2021) - 2020
- [c15]Prashnna Kumar Gyawali, Sandesh Ghimire, Linwei Wang:
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization. ICDM 2020: 1046-1051 - [c14]Xiajun Jiang, Sandesh Ghimire, Jwala Dhamala, Zhiyuan Li, Prashnna Kumar Gyawali, Linwei Wang:
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction. MICCAI (6) 2020: 487-496 - [c13]Prashnna Kumar Gyawali, Sandesh Ghimire, Pradeep Bajracharya, Zhiyuan Li, Linwei Wang:
Semi-supervised Medical Image Classification with Global Latent Mixing. MICCAI (1) 2020: 604-613 - [c12]Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu, Alexandros Karargyris, Mehdi Moradi:
Learning Invariant Feature Representation to Improve Generalization Across Chest X-Ray Datasets. MLMI@MICCAI 2020: 644-653 - [i13]Sandesh Ghimire, Prashnna K. Gyawali, Linwei Wang:
Reliable Estimation of Kullback-Leibler Divergence by Controlling Discriminator Complexity in the Reproducing Kernel Hilbert Space. CoRR abs/2002.11187 (2020) - [i12]Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang:
High-dimensional Bayesian Optimization of Personalized Cardiac Model Parameters via an Embedded Generative Model. CoRR abs/2005.07804 (2020) - [i11]Prashnna Kumar Gyawali, Sandesh Ghimire, Pradeep Bajracharya, Zhiyuan Li, Linwei Wang:
Semi-supervised Medical Image Classification with Global Latent Mixing. CoRR abs/2005.11217 (2020) - [i10]Xiajun Jiang, Sandesh Ghimire, Jwala Dhamala, Zhiyuan Li, Prashnna Kumar Gyawali, Linwei Wang:
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction. CoRR abs/2007.09522 (2020) - [i9]Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu, Alexandros Karargyris, Mehdi Moradi:
Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets. CoRR abs/2008.04152 (2020) - [i8]Prashnna Kumar Gyawali, Sandesh Ghimire, Linwei Wang:
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization. CoRR abs/2009.11416 (2020)
2010 – 2019
- 2019
- [j1]Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang:
Noninvasive Reconstruction of Transmural Transmembrane Potential With Simultaneous Estimation of Prior Model Error. IEEE Trans. Medical Imaging 38(11): 2582-2595 (2019) - [c11]Prashnna K. Gyawali, Zhiyuan Li, Cameron Knight, Sandesh Ghimire, B. Milan Horácek, John L. Sapp, Linwei Wang:
Improving Disentangled Representation Learning with the Beta Bernoulli Process. ICDM 2019: 1078-1083 - [c10]Sandesh Ghimire, Prashnna Kumar Gyawali, Jwala Dhamala, John L. Sapp, Milan Horacek, Linwei Wang:
Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences. IPMI 2019: 153-166 - [c9]Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang:
Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization. MICCAI (2) 2019: 458-467 - [c8]Prashnna Kumar Gyawali, Zhiyuan Li, Sandesh Ghimire, Linwei Wang:
Semi-supervised Learning by Disentangling and Self-ensembling over Stochastic Latent Space. MICCAI (6) 2019: 766-774 - [i7]Sandesh Ghimire, Prashnna Kumar Gyawali, Jwala Dhamala, John L. Sapp, Milan Horacek, Linwei Wang:
Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences. CoRR abs/1903.02948 (2019) - [i6]Sandesh Ghimire, Jwala Dhamala, Prashnna Kumar Gyawali, John L. Sapp, B. Milan Horácek, Linwei Wang:
Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential. CoRR abs/1905.04803 (2019) - [i5]Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang:
Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization. CoRR abs/1907.01406 (2019) - [i4]Prashnna Kumar Gyawali, Zhiyuan Li, Sandesh Ghimire, Linwei Wang:
Semi-Supervised Learning by Disentangling and Self-Ensembling Over Stochastic Latent Space. CoRR abs/1907.09607 (2019) - [i3]Prashnna Kumar Gyawali, Zhiyuan Li, Cameron Knight, Sandesh Ghimire, B. Milan Horácek, John L. Sapp, Linwei Wang:
Improving Disentangled Representation Learning with the Beta Bernoulli Process. CoRR abs/1909.01839 (2019) - 2018
- [c7]Sandesh Ghimire, Linwei Wang:
Deep Generative Modeling and Analysis of Cardiac Transmembrane Potential. CinC 2018: 1-4 - [c6]Jwala Dhamala, Sandesh Ghimire, John L. Sapp, B. Milan Horácek, Linwei Wang:
High-Dimensional Bayesian Optimization of Personalized Cardiac Model Parameters via an Embedded Generative Model. MICCAI (2) 2018: 499-507 - [c5]Sandesh Ghimire, Jwala Dhamala, Prashnna Kumar Gyawali, John L. Sapp, Milan Horacek, Linwei Wang:
Generative Modeling and Inverse Imaging of Cardiac Transmembrane Potential. MICCAI (2) 2018: 508-516 - [i2]Sandesh Ghimire, Prashnna Kumar Gyawali, John L. Sapp, Milan Horacek, Linwei Wang:
Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential. CoRR abs/1810.05713 (2018) - [i1]Prashnna K. Gyawali, Cameron Knight, Sandesh Ghimire, B. Milan Horácek, John L. Sapp, Linwei Wang:
Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factors. CoRR abs/1811.00073 (2018) - 2017
- [c4]Jwala Dhamala, Jaume Coll-Font, Jess D. Tate, María de la Salud Guillem Sánchez, Dana H. Brooks, Linwei Wang, Rob S. MacLeod, Sandesh Ghimire:
Overcoming Barriers to Quantification and Comparison of Electrocardiographic Imaging Methods: a Community-Based Approach. CinC 2017 - [c3]Sandesh Ghimire, Linwei Wang:
L_0 Norm Based Sparse Regularization for Non-invasive Infarct Detection Using ECG Signal. CinC 2017 - [c2]Sandesh Ghimire, John L. Sapp, Milan Horacek, Linwei Wang:
A Variational Approach to Sparse Model Error Estimation in Cardiac Electrophysiological Imaging. MICCAI (2) 2017: 745-753 - 2016
- [c1]Linwei Wang, Omar Gharbia, Sandesh Ghimire, Milan Horacek, John L. Sapp:
Noninvasive Epicardial and Endocardial Electrocardiographic Imaging of Scar-Related Ventricular Tachycardia. CinC 2016
Coauthor Index
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