5 citations · 7 across the 5 of their papers we have counts for
5 papers
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…
Differentiable Uncalibrated Imaging
Sidharth Gupta, Konik Kothari, Valentin Debarnot +1
We propose a differentiable imaging framework to address uncertainty in measurement coordinates such as sensor locations and projection angles. We formulate the problem as measurem…
Small Transformers Compute Universal Metric Embeddings
Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić
We study representations of data from an arbitrary metric space in the space of univariate Gaussian mixtures with a transport metric (Delon and Desolneux 2020). We de…
Manifold Rewiring for Unlabeled Imaging
Valentin Debarnot, Vinith Kishore, Cheng Shi +1
Geometric data analysis relies on graphs that are either given as input or inferred from data. These graphs are often treated as "correct" when solving downstream tasks such as gra…
Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography
Shuai Huang, Mona Zehni, Ivan Dokmanić +1
Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations. A line of work starting with Kam (1980) employs the method of m…