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Works (12)

Semi-Supervised Deep Expectation-Maximization for Low-Dose Pet-Ct

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
2022 | Conference paper
Source: Self-asserted source
Ansh Khurana

Symbolic Binding in Neural Networks through Factorized Memory Systems

2022 | Journal article
Source: Self-asserted source
Ansh Khurana

What can we do with just the model? A simple knowledge extraction framework

2022 | Journal article
Source: Self-asserted source
Ansh Khurana

SEMI-SUPERVISED DEEP EXPECTATION-MAXIMIZATION FOR LOW-DOSE PET-CT

2022-01-01 | Conference paper
DOI: 10.1109/ISBI52829.2022.9761601
WOSUID:

WOS:000836243800199

Part of ISSN: 1945-7928
Contributors: Sharma, Vatsala; Khurana, Ansh; Yenamandra, Sriram; Awate, Suyash P.
Source: check_circle
Stanford University

Learning Image Inpainting from Incomplete Images using Self-Supervision

2020 25th International Conference on Pattern Recognition (ICPR)
2021 | Conference paper
Source: Self-asserted source
Ansh Khurana

Multi-stage Fusion for One-Click Segmentation

2021 | Book chapter
DOI: 10.1007/978-3-030-71278-5_13
Contributors: Soumajit Majumder; Ansh Khurana; Abhinav Rai; Angela Yao
Source: check_circle
Crossref

Sita: Single image test-time adaptation

arXiv preprint arXiv:2112.02355
2021 | Journal article
Source: Self-asserted source
Ansh Khurana

Unsupervised Adaptation of Semantic Segmentation Models without Source Data

arXiv preprint arXiv:2112.02359
2021 | Journal article
Source: Self-asserted source
Ansh Khurana

Learning Image Inpainting from Incomplete Images using Self-Supervision

2021-01-01 | Conference paper
DOI: 10.1109/ICPR48806.2021.9413049
WOSUID:

WOS:000681331402118

Part of ISSN: 1051-4651
Contributors: Yenamandra, Sriram; Khurana, Ansh; Jena, Rohit; Awate, Suyash P.
Source: check_circle
Stanford University

Selecting Influential Features by a Learnable Content-Aware Linear Threshold Model

Proceedings of the 29th ACM International Conference on Information & Knowledge Management
2020 | Conference paper
Source: Self-asserted source
Ansh Khurana

Two-in-One Refinement for Interactive Segmentation

BMVC
2020 | Conference paper
Source: Self-asserted source
Ansh Khurana

Selecting Influential Features by a Learnable Content-Aware Linear Threshold Model

2020-01-01 | Conference paper
DOI: 10.1145/3340531.3411886
WOSUID:

WOS:000749561300066
Contributors: Khurana, Ansh; Logins, Alvis; Karras, Panagiotis
Source: check_circle
Stanford University
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