IEEE

Sparse Bayesian learning for basis selection

Abstract: Sparse Bayesian learning (SBL) and specifically relevance vector machines have received much attention in the machine learning literature as a means of achieving parsimonious representations ...
IEEE

Sparse Bayesian Learning-Based Seismic High-Resolution Time-Frequency Analysis

Abstract: Time-frequency (TF) analysis is a useful tool for seismic data processing and interpretation. We introduce sparse Bayesian learning (SBL) to TF analysis and propose a new SBL-based ...
GitHub

Ruiting-Xiao/Deep-Unfolding-Methods-for-Sparse-Bayesian-Learning-in-M-EEG-Inverse-Modeling

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...
GitHub

bylan-lab/Radio-Map-Reconstruction_CS-SBL

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...
Nature

The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century

The word 'statistics' has two meanings—the use of numbers to describe whole patterns of activity (for example, baseball statistics), and the analytic methods that allow manipulation of such data. The ...
AlphaGalileo

AI sharpens solar radiation mapping from space

Accurate sunlight data is becoming essential for the clean-energy transition, but tracking how much solar radiation reaches ...
Technology Networks

Predictive Modeling for Compound Prioritization

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...
BMJ Open

Protocol for the economic evaluation of integrated longitudinal public health interventions ...

Introduction In 2021, globally, cardiometabolic diseases (CMDs) accounted for 35% of the 1.73 billion disability-adjusted life years (DALYs) attributed to non-communicable diseases. The Healthy Life ...