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Meet renowned US-based statistics and computer science expert who joins Fields Medalist Ngo Bao Chau to mentor Vietnamese math talents

Nguyen Xuan Long, a globally recognized expert in statistical inference and machine learning currently based in the United ...

From LLMs to hallucinations, here’s a simple guide to common AI terms

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
IEEE

Bayesian Muography Incorporating Prior Knowledge: A High-Resolution Imaging Algorithm for Structurally Complex Cultural Artifacts

Abstract: Cultural artifacts are vital for heritage preservation but vulnerable to environmental damage that creates internal structural defects not visible on the surface. The drainage dragon heads ...
Digi Times

In-depth: Google TurboQuant cuts LLM memory 6x, resets AI inference cost curve

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...
GitHub

Be Bayesian my Friend 2.0.

The course is structured in four main parts, covering the full Bayesian workflow: from probabilistic reasoning to advanced modeling. BAYESIANLEARNING/ │ ├── PART-I/ │ ├── theory/ │ │ └── ...
IEEE

Variational Bayesian Sparse Decision-Feedback Equalization Based on RLS Algorithm in Underwater Acoustic Communications

Abstract: This letter proposes a variational Bayesian sparse decision-feedback equalizer (VB-SDFE) based on the recursive least squares (RLS) algorithm for underwater acoustic communications. The ...
TechCrunch

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
GitHub

psoerensen/bayesian-linear-regression

This repository includes theoretical notes, slides, and hands-on R examples for exploring Bayesian Linear Regression. It introduces both classical and Bayesian regression methods, showing how to ...