Slice Sampling

Slice sampling is a Markov Chain Monte Carlo (MCMC) method used to draw samples from probability distributions, particularly those that are difficult to sample directly. Current research focuses on improving the efficiency and robustness of slice sampling algorithms, especially for high-dimensional data and complex distributions, with advancements in elliptical slice sampling and its application within various model architectures like transformers and diffusion models. These improvements are driving applications in diverse fields, including medical imaging (accelerated MRI, COVID-19 detection), computer vision (hand mesh reconstruction, object detection), and robotics (probabilistic verification of autonomous systems), where efficient sampling is crucial for accurate and timely analysis.