This tutorial introduces the reader to Gaussian process regression as an expressive tool to
model, actively explore and exploit unknown functions. Gaussian process regression is a …

Cognitive tasks are capable of providing researchers with crucial insights into the
relationship between cognitive processing and psychiatric phenomena. However, many …

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 …

Tackling the most pressing problems for humanity, such as the climate crisis and the threat
of global pandemics, requires accelerating the pace of scientific discovery. While science …

Abstract We introduce Deep Adaptive Design (DAD), a method for amortizing the cost of
adaptive Bayesian experimental design that allows experiments to be run in real-time …

What are the principles that govern whether neural representations move apart
(differentiate) or together (integrate) as a function of learning? According to supervised …

Bayesian experimental design (BED) provides a powerful and general framework for
optimizing the design of experiments. However, its deployment often poses substantial …

Bringing precision to the understanding and treatment of mental disorders requires
instruments for studying clinically relevant individual differences. One promising approach is …

Bayesian optimal experimental design (BOED) is a principled framework for making efficient
use of limited experimental resources. Unfortunately, its applicability is hampered by the …

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for
hypothesis evaluation and model selection. The present review highlights the potential of …