Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Abstract: Like other machine learning methods, Genetic Programming (GP) frequently faces the issue of overfitting when applied to supervised learning tasks. Traditional regularization techniques, ...

Who's trying to build superintelligent AI? Companies such as Google, OpenAI, Meta, and Anthropic have collectively dedicated more than $1 trillion to developing artificial general intelligence (AGI).

The creaminess of custard. The fizz of foam. The slurpability of soup. Texture is just as essential to our eating experience as flavor and smell. But it’s notoriously difficult to predict the ...