Mental math's shortcut—pupil dilation suggests people start solving before all numbers are in

People often solve simple arithmetic problems, such as basic addition, subtraction, multiplication or division, in their ...
Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
InfoQ

Google Researchers Propose Bayesian Teaching Method for Large Language Models

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...
IEEE

Variational Bayesian inference -Based Maximum Correntropy Kalman Filtering for Visual Tracking with Unknown Process and measurement Noise

Abstract: The paper proposes a new Kalman filtering (KF) algorithm called VBI-MCKF that combines the variational Bayesian inference (VBI)-based KF algorithm and the maximum correntropy KF (MCKF) for ...
eLife

Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models

This paper presents a valuable software package, named "Virtual Brain Inference" (VBI), that enables faster and more efficient inference of parameters in dynamical system models of whole-brain ...
Frontiers

A hierarchical Bayesian inference model for volatile multivariate exponentially distributed signals

Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The ...
CNBC

Equinix CEO: AI inference in business process needs connectivity which we do

Adaire Fox-Martin, Equinix CEO, joins 'Power Lunch' to discuss Equinix's role in the data center world, the 'secret sauce' of the company and much more. Got a confidential news tip? We want to hear ...
Scientific Research Publishing

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference.

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
Oak Ridge National Lab

Deployed quantum link characterization via Bayesian ancilla-assisted process tomography

The development of large-scale quantum networks requires reliable quantum channels, the quality of which can be quantified by the framework of quantum process tomography. In this work, we leverage ...