Tag: Machine learning

A new tensor decomposition framework dynamically compresses and decompresses neural network layers during training, achieving 95.81 percent accuracy in 12 ...

Researchers have developed P2CE, a model-agnostic algorithm that generates counterfactual explanations for machine learning decisions that are both plausible and ...

Researchers have developed a noise-robust over-sampling method called mZ-cEAMD that outperforms SMOTE-based techniques in classifying defective car transmissions from severely ...

A new study shows that AI voice cloning systems preserve not only speaker identity but also the human-specific prosodic cues ...

Researchers have built a machine learning framework that predicts context-specific synthetic lethal vulnerabilities between paralog gene pairs across 1,005 cancer ...

A comprehensive new review shows how machine learning and deep learning are transforming marine biodiversity monitoring, fisheries management, pollution detection ...

Researchers have developed a hybrid LSTM–PINN artificial intelligence model that accurately and rapidly predicts the violent impact loads and motion ...

A knowledge–data dual-driven machine learning framework combining deep forest algorithms with orogenic gold mineral system knowledge has improved mineral prospectivity ...

Researchers at Yanshan University have developed a multi-objective multitasking optimization algorithm that uses adaptive knowledge transfer and manifold learning to ...

An interpretable machine learning model trained on 20 years of rural Spanish registry data outperforms logistic regression in predicting 30-day ...