The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

The mathematical form of many optimization problems in engineering is constrained optimization problems. In this paper, an improved genetic algorithm based on two-direction crossover and grouped ...

In the realm of medicinal chemistry, the predominant challenge in molecular design lies in managing extensive molecular data sets and effectively screening for, as well as preserving, molecules with ...

Learn how to implement Adam optimization from the ground up in Python! This step-by-step guide will walk you through the algorithm's mechanics and how to use it in machine learning projects. 🚀 ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

Luke Fox: The goal of using the genetic algorithm was to create an optimal massing that prioritized the creation of a central public square and maximized views for the building's occupants.

An interactive web app for visualizing and optimizing solutions using genetic algorithms, featuring customizable parameters, real-time visualizations, and support for various objective functions.