AlphaGalileo

Fast AI for satellite learns to quantify uncertainty

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

X open sources its algorithm while facing a transparency fine and Grok controversies

In 2023, the website then known as Twitter partially open sourced its algorithm for the first time. In those days, Tesla ...
IEEE

Machine-Learning-Based Algorithm for Significant Wave Height Retrieval From Microwave Radiometer During Tropical Cyclones

This study develops a machine-learning-based approach to retrieve significant wave height (SWH) from soil moisture active passive (SMAP) radiometer data under tropical cyclone (TC) conditions, ...
Frontiers

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
IEEE

Decoding Machine Learning Algorithms for DR Detection

Abstract: Diabetic retinopathy is a serious eye disease which can lead to vision defects in diabetic patients. Early detection is important for preventing vision loss. Automating the detection process ...