A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk. The ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

The Society for Financial Econometrics (SoFiE) Summer School is an annual week-long research-based course for PhD students, new faculty, and professionals in financial econometrics. For the first two ...

Quantum machine learning is a hybrid approach that combines classical data with quantum computing methods. In classical computing, data is stored in bits encoded as a 0 or 1. Quantum computers use ...

Department of Chemistry, Graduate School of Science, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan Molecular Photoscience Research Center, Kobe University, 1-1, Rokkodai-cho, ...

Abstract: Convolutional neural networks (CNNs) have played a significant role in the recent evolution of machine learning (ML) due to their feature extraction and pattern recognition capabilities.

Welcome to AI HUB’s new series on “Machine Learning from Scratch”. Here we will include a full Table of contents of Machine Learning from the Scratch tutorial series. Here we will cover all the ...

The success of a molecular dynamics simulation depends on the accuracy of the force field used to define the atomic interactions. It is challenging to train both classical and modern machine-learning ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...