Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...

Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Written in Python, Freqtrade is a free, open-source crypto trading bot that works with all major exchanges and can be operated using Telegram or WebUI. It is great at automating tactics through ...

Abstract: This study addresses the optimization of hyperparameter selection in machine learning models designed to predict psychological characteristics (e.g., “Big Five” traits) from social media ...

OS-R1 is an agentic Linux kernel tuning framework that leverages reinforcement learning (RL) and large language models (LLMs) for efficient kernel configuration. It introduces a rule-based RL approach ...

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 ...

Abstract: Hyperparameter tuning is a crucial step in the development of machine learning models, as it directly impacts their performance and generalization ability. Traditional methods for ...