Text-based CAPTCHA has become one of the most popular methods for preventing bot
attacks. With the rapid development of deep learning techniques, many new methods to …

How can one perform Bayesian inference on stochastic simulators with intractable
likelihoods? A recent approach is to learn the posterior from adaptively proposed …

The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging
cellular structures with nanometer resolution, but standard analysis algorithms require …

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of
underlying causes. However, determining which model parameters agree with complex and …

Monocular depth estimation using learning-based approaches has become promising in
recent years. However, most monocular depth estimators either need to rely on large …

This book is a graduate-level introduction to probabilistic programming. It not only provides a
thorough background for anyone wishing to use a probabilistic programming system, but …

Although atrial fibrillation (AF) is the most common cardiac arrhythmia, its early identification,
diagnosis, and treatment is still challenging. Due to its heterogeneous mechanisms and risk …

Despite several attacks have been proposed, text-based CAPTCHAs are still being widely
used as a security mechanism. One of the reasons for the pervasive use of text captchas is …

Abstract Approximate Bayesian Computation (ABC) provides methods for Bayesian
inference in simulation-based models which do not permit tractable likelihoods. We present …