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Shayan Shekarforoush
Shayan Shekarforoush
PhD Student, University of Toronto, Vector Institute
Verified email at cs.toronto.edu - Homepage
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Cited by
Year
InceptionGCN: receptive field aware graph convolutional network for disease prediction
A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ...
IPMI 2019, 73-85, 2019
1762019
Graph convolution based attention model for personalized disease prediction
A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ...
MICCAI 2019, 122-130, 2019
482019
Self-Attention Equipped Graph Convolutions for Disease Prediction
A Kazi, S Shekarforoush, K Kortuem, S Albarqouni, N Navab
ISBI 2019, 1896-1899, 2019
452019
Residual Multiplicative Filter Networks for Multiscale Reconstruction
S Shekarforoush, DB Lindell, DJ Fleet, MA Brubaker
NeurIPS 2022, 2022
182022
Dual-Camera Joint Deblurring-Denoising
S Shekarforoush, A Walia, MA Brubaker, KG Derpanis, A Levinshtein
arXiv preprint arXiv:2309.08826, 2023
52023
Physics aware inference for the cryo-EM inverse problem: anisotropic network model heterogeneity, global pose and microscope defocus
G Woollard, S Shekarforoush, F Wood, MA Brubaker, KD Duc
NeurIPS Workshop on Machine Learning for Structural Biology, 2022
22022
Dual-Camera Joint Denoising-Deblurring Using Burst of Short and Long Exposure Images
S Shekarforoush, AS Walia, A Levinshtein, KG Derpanis, MA Brubaker
US Patent App. 18/387,964, 2024
2024
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
S Shekarforoush, DB Lindell, MA Brubaker, DJ Fleet
NeurIPS 2024, 2024
2024
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Articles 1–8