3 papers
stat.ME2026
Self-Supervised Conformal Prediction with Equivariant Bootstrapping for Image Uncertainty Quantification
Henry J. Aldridge, TobÃas I. Liaudat, Marcelo Pereyra +1
Inverse problems are ubiquitous in modern scientific studies and involve recovering an underlying signal from noisy observations often transformed by a measurement operator. These…
eess.IV2025
Normalization-equivariant Diffusion Models: Learning Posterior Samplers From Noisy And Partial Measurements
Brett Levac, Jon Tamir, Marcelo Pereyra +1
Diffusion models (DMs) have rapidly emerged as a powerful framework for image generation and restoration. However, existing DMs are primarily trained in a supervised manner by usin…
stat.ME2025
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Hong Ye Tan, Ziruo Cai, Marcelo Pereyra +3
Imaging is a standard example of an inverse problem, where the task of reconstructing a ground truth from a noisy measurement is ill-posed. Recent state-of-the-art approaches for i…