Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Guizhou Education University, Guiyang 550018, P. R. China ...

Gaussian Graphical Models (GGMs) are a type of network modeling that uses partial correlation rather than correlation for representing complex relationships among multiple variables. The advantage of ...

[Nov 7, 2025] GM-Qwen-Image and GM-FLUX is now available for ComfyUI via the ComfyUI-piFlow extension. Supports 4-step sampling of Qwen-Image and Flux.1 dev using 8-bit models on a single ...

Signals composed of a sum of sinusoids are often used when testing components and systems. The peak-to-RMS value of the sum stresses the dynamic range of the component or system, thus correcting a ...

Quantum cryptography has emerged as a radical research field aimed at mitigating various security threats in modern communication systems. The integration of Quantum Machine Learning (QML) protocols ...

ABSTRACT: Federated Learning (FL), which serves as a distributed learning model focused on privacy protection, has received widespread attention due to its ability to collaboratively train models ...