Abstract: A Bayesian method for texture model choice from blurred and noisy (i.e., indirect) observations is presented. The textures are modeled by stationary Random Fields, with various distribution ...

This repository is the official implementation for the paper: How does Bayesian Sampling help Membership Inference Attacks? at ICML 2026. This codebase has been tested on Ubuntu 22.04.5 LTS with ...

Sampling from a target probability distribution is fundamental to modern computational science and machine learning. Sampling is the essence of Monte Carlo integration, enables uncertainty ...

Dr. Weatherby is the director of the Digital Theory Lab at New York University. Dr. Recht is a professor of electrical engineering and computer sciences at the University of California, Berkeley. See ...

Advances in plant imaging and computer vision have transformed agriculture and biology by enabling continuous and objective trait quantification. However, monitoring large plant populations or ...

Numerical optimization plays a vital role in the design of complex engineered systems. Real world engineered systems are seldom designed based on a single objective; rather they involve multiple ...

Abstract: Machine learning (ML) has demonstrated significant potential in accelerating the design of microwave components owing to its great ability to approximate the projection between geometric ...

Within neuroscience, psychology, and neuroimaging, the most frequently used statistical approach is null hypothesis significance testing (NHST) of the population mean. An alternative approach is to ...

Random tomography is a common problem in imaging science and refers to the task of reconstructing a three-dimensional volume from two-dimensional projection images acquired in unknown random ...