"Deep Learning for Physics Research" balances theory and practice, physics and programming, and foundations and state-of-the-art deep-learning concepts.
The CERN-developed simulator “Molflow” has become the de-facto industry standard for ultra-high-vacuum simulations, with applications ranging from chip manufacturing to the exploration of the Mart...
The structure was designed to stimulate sew insights, dialogue and collaboration between AI specialists, scientists, philosophers and ethicists.
Exploring the potential of quantum information science and technologies for high-energy physics.
SKAO director-general Philip Diamond describes how the world's largest radio telescope went from concept to construction.
Headed by two ATLAS physicists, gluoNNet applies data-mining and machine-learning techniques to benefit wider society.
A new CMS analysis searches for anomalies in top-quark interactions with the Z boson using an effective-field-theory framework.
Erik Verlinde sizes up the Standard Model, gravity and intelligence as candidates for future explanation as emergent phenomena.
Time-stamped files stated by Tim Berners-Lee to contain the original source code for the web and digitally signed by him, have sold for US$5.4 million at auction.
Jesse Thaler argues that particle physicists must go beyond deep learning and design AI capable of deep thinking.