2 citations · 3 across the 5 of their papers we have counts for
5 papers
Minimax Multi-Target Conformal Prediction with Applications to Imaging Inverse Problems
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
In ill-posed imaging inverse problems, uncertainty quantification remains a fundamental challenge, especially in safety-critical applications. Recently, conformal prediction has be…
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
Jeffrey Wen, Rizwan Ahmad, Philip Schniter
In imaging inverse problems, we would like to know how close the recovered image is to the true image in terms of full-reference image quality (FRIQ) metrics like PSNR, SSIM, LPIPS…
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…
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…
Diamond in the rough: Improving image realism by traversing the GAN latent space
Jeffrey Wen, Fabian Benitez-Quiroz, Qianli Feng +1
In just a few years, the photo-realism of images synthesized by Generative Adversarial Networks (GANs) has gone from somewhat reasonable to almost perfect largely by increasing the…