The science of how (and when) we decide to speak out—or self-censor

Researchers explored the nuanced dynamics of how people balance their desire to speak out vs their fear of punishment in a ...
Learn With Jay on MSNOpinion

Supervised learning made easy: Real-world example explained

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...
IEEE

SDCNN: Self-Supervised Disentangled Convolutional Neural Network for Low-Dose CT Denoising

Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from high noise, impacting image quality and diagnostic accuracy. Supervised learning has helped address this challenge but ...
GitHub

Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video Denoising

This repository contains the official implementation of our paper "Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video Denoising". Self-supervised video ...
International Monetary Fund

A Python Package to Assist Macroframework Forecasting: Concepts and Examples

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...
Electrek

Elon Musk teases new Tesla ‘Full Self-Driving Supervised’, but manage your expectations

Elon Musk is teasing a new Tesla ‘Full Self-Driving Supervised’ (FSD) update with “10x improvements”, but historical performance compared to Musk’s announcements suggests that it’s safer to manage ...
Wired

This AI Model Never Stops Learning

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...
IEEE

Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples

Abstract: Semi-supervised learning (SSL) methods have shown promising results in solving many practical problems when only a few labels are available. The existing methods assume that the class ...