The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

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 ...

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: Learning-based motion planning methods have shown significant promise in enhancing the efficiency of traditional algorithms. However, they often face performance degradation in novel ...

Abstract: Offline reinforcement learning (RL) learns policies from fixed-size datasets without interacting with the environment, while multi-agent reinforcement learning (MARL) faces challenges from ...

“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...