527 citations · 3.5k across the 52 of their papers we have counts for
58 papers
Score Combining for Contrastive OOD Detection
Edward T. Reehorst, Philip Schniter
In out-of-distribution (OOD) detection, one is asked to classify whether a test sample comes from a known inlier distribution or not. We focus on the case where the inlier distribu…
Fast and Robust Phase Retrieval via Deep Expectation-Consistent Approximation
Saurav K. Shastri, Philip Schniter
Accurately recovering images from phaseless measurements is a challenging and long-standing problem. In this work, we present "deepECpr," which combines expectation-consistent (EC)…
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
In imaging inverse problems, one seeks to recover an image from missing/corrupted measurements. Because such problems are ill-posed, there is great motivation to quantify the uncer…
Surface Coil Intensity Correction for MRI
Xuan Lei, Philip Schniter, Chong Chen +2
Modern MRI scanners utilize one or more arrays of small receive-only coils to collect k-space data. The sensitivity maps of the coils, when estimated using traditional methods, dif…
A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
Accelerated magnetic resonance (MR) imaging attempts to reduce acquisition time by collecting data below the Nyquist rate. As an ill-posed inverse problem, many plausible solutions…
MRI Recovery with Self-Calibrated Denoisers without Fully-Sampled Data
Muhammad Shafique, Sizhuo Liu, Philip Schniter +1
Objective: Acquiring fully sampled training data is challenging for many MRI applications. We present a self-supervised image reconstruction method, termed ReSiDe, capable of recov…