1 citations · 2 across the 5 of their papers we have counts for
6 papers
Marginal Flow: a flexible and efficient framework for density estimation
Marcello Massimo Negri, Jonathan Aellen, Manuel Jahn +2
Current density modeling approaches suffer from at least one of the following shortcomings: expensive training, slow inference, approximate likelihood, mode collapse or architectur…
Localized Supervised Learning for Cryo-ET Reconstruction
Vinith Kishore, Valentin Debarnot, AmirEhsan Khorashadizadeh +1
Cryo-electron tomography (Cryo-ET) is a powerful tool in structural biology for 3D visualization of cells and biological systems at resolutions sufficient to identify individual pr…
CryoLithe: Rapid Cryo-ET Reconstruction via Transform-Localized Deep Learning
Vinith Kishore, Valentin Debarnot, AmirEhsan Khorashadizadeh +3
Cryo-electron tomography (cryo-ET) enables 3D visualization of cellular structures. Accurate reconstruction of high-resolution volumes is complicated by the very low signal-to-nois…
LoFi: Neural Local Fields for Scalable Image Reconstruction
AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu +2
Neural fields or implicit neural representations (INRs) have attracted significant attention in computer vision and imaging due to their efficient coordinate-based representation o…
Glimpse: Generalized Locality for Scalable and Robust CT
AmirEhsan Khorashadizadeh, Valentin Debarnot, Tianlin Liu +1
Deep learning has become the state-of-the-art approach to medical tomographic imaging. A common approach is to feed the result of a simple inversion, for example the backprojection…
Deep Variational Inverse Scattering
AmirEhsan Khorashadizadeh, Ali Aghababaei, Tin Vlašić +2
Inverse medium scattering solvers generally reconstruct a single solution without an associated measure of uncertainty. This is true both for the classical iterative solvers and fo…