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

Assessing the progress of new AI language models can be as challenging as training them. Stanford researchers offer a new approach.

Nanoparticles—the tiniest building blocks of our world—are constantly in motion, bouncing, shifting, and drifting in ...

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

AI introduces a dynamic, context-aware, and data-driven approach to capital allocation. Using machine learning algorithms, ...

This study uses five Machine Learning classification algorithms (Gaussian Naive Bayes, AdaBoost, Gradient Boosting, K Neighbors Classifier, Decision Trees, Random Forest, and Logistic Regression) and ...

Traditional meta-heuristics have good performance on solving black box problems with flexibility, derivation-free mechanism and local optima avoidance. How-ever, due to the simplicity of most models, ...

To investigate the intrinsic role of EPS in fouling, a predictive membrane fouling model was developed using a supervised learning algorithm trained on experimental EPS data sets. After hyperparameter ...

A Laboratory-wide collaborative community of AI researchers and applied scientists works in domains from beneath the sea to outer space to innovatively incorporate autonomy, computer vision, machine ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.