18 citations · 27 across the 4 of their papers we have counts for
6 papers
Reconstructing Heterogeneous Biomolecules via Hierarchical Gaussian Mixtures and Part Discovery
Shayan Shekarforoush, David B. Lindell, Marcus A. Brubaker +1
Cryo-EM is a transformational paradigm in molecular biology where computational methods are used to infer 3D molecular structure at atomic resolution from extremely noisy 2D electr…
CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
Shayan Shekarforoush, David B. Lindell, Marcus A. Brubaker +1
Cryo-EM is an increasingly popular method for determining the atomic resolution 3D structure of macromolecular complexes (eg, proteins) from noisy 2D images captured by an electron…
Dual-Camera Joint Deblurring-Denoising
Shayan Shekarforoush, Amanpreet Walia, Marcus A. Brubaker +2
Recent image enhancement methods have shown the advantages of using a pair of long and short-exposure images for low-light photography. These image modalities offer complementary s…
Residual Multiplicative Filter Networks for Multiscale Reconstruction
Shayan Shekarforoush, David B. Lindell, David J. Fleet +1
Coordinate networks like Multiplicative Filter Networks (MFNs) and BACON offer some control over the frequency spectrum used to represent continuous signals such as images or 3D vo…
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
Anees Kazi, Shayan shekarforoush, S. Arvind krishna +6
Geometric deep learning provides a principled and versatile manner for the integration of imaging and non-imaging modalities in the medical domain. Graph Convolutional Networks (GC…
Self-Attention Equipped Graph Convolutions for Disease Prediction
Anees Kazi, S. Arvind krishna, Shayan Shekarforoush +3
Multi-modal data comprising imaging (MRI, fMRI, PET, etc.) and non-imaging (clinical test, demographics, etc.) data can be collected together and used for disease prediction. Such…