How ‘catchy’ music is driven by rhythmic patterns

Catchy rhythms like the tresillo are examples of how our musical perception and preference negotiate between simplicity and ...
eLife

Bayesian causal inference unifies perceptual and neuronal processing of center-surround motion in area MT

This manuscript represents a valuable contribution to understanding motion processing in the visual cortex. Based on a heterogeneous collection of previous empirical findings, the authors show that ...
IEEE

Cautious Bayesian MPC: Regret Analysis and Bounds on the Number of Unsafe Learning Episodes

Abstract: This article investigates the combination of model predictive control (MPC) concepts and posterior sampling techniques and proposes a simple constraint tightening technique to introduce ...
Undark

Why the FDA Is Embracing Old Math for New Drugs

Clinical trials for a new drug can take years to complete, and cost up to hundreds of millions of dollars. New draft guidance from the U.S. Food and Drug Administration aims to make that process ...
Investopedia

How to Use Bayesian Methods for Accurate Financial Forecasting

Daniel McNulty began writing for Investopedia in 2012. His work includes articles on financial analysis, asset allocation, and trading strategies. Marguerita is a Certified Financial Planner (CFP), ...
Nature

Bayesian teaching enables probabilistic reasoning in large language models

Humans interact with the world based on our beliefs about it. To effectively support decision making, our beliefs need to correspond to the structure of the world as much as possible; in other words, ...
Hosted on MSN

A simple explanation of Bayes’ theorem anyone can understand

Get a simple explanation of Bayes’ Theorem that anyone can understand, even with no advanced math background. This video breaks the idea down using clear examples and intuitive reasoning to show how ...
GitHub

Bayesian Optimization & Analysis of Hyperparameters

This repository provides simple examples of how to construct a configuration space using the ConfigSpace package, how to use BOHB with minimal efforts and how to run CAVE to generate a comprehensive ...
Physics World

Bayes’ rule goes quantum

What would Thomas Bayes think? In 1763, he proposed a new approach to calculate probabilities. An international team has now updated his ideas to deliver a quantum Bayes' rule. (Courtesy: Centre for ...
GitHub

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable Bayesian inference in deep learning models to quantify principled uncertainty estimates in ...
Investopedia

Conditional Probability: Formula and Real-Life Examples

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Thomas J Catalano is a CFP and Registered ...