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

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

New data-driven map uses live weather, water temperature modeling, and machine learning to help prevent fish loss ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.

A particle collision reconstructed using the new CMS machine-learning-based particle-flow (MLPF) algorithm. The HFEM and HFHAD signals come from the ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

BANGALORE, India , Feb. 17, 2026 /PRNewswire/ -- According to Valuates Reports, The global market for AI in Biotechnology was valued at USD 1033 Million in the year 2024 and is projected to reach a ...

Electra announces a major milestone with the successful validation of its EVE‑Ai™ Adaptive Controls platform, enabling ...