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 ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

A team of EPFL researchers has developed an AI algorithm capable of modelling complex dynamical processes while adhering to the laws of physics—specifically Newton’s third law.

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron densities By applying new methods of machine learning in quantum chemistry ...

Integrating deep learning with traditional forecasting techniques can improve early warning systems by capitalizing on each ...

Another theory held that the forces between two particles falls off exponentially in direct relationship to the distance between two particles and that the factor by which it drops is not dependent on ...

Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left ...

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

Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...