Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
EurekAlert!

All-in-focus fourier ptychographic microscopy via 3D implicit neural representation

Microscopy plays a pivotal role in modern biomedical research, enabling the visualization of fine structures in complex ...
Forbes

Neural Networks Co-Inventor Geoffrey Hinton Wins Physics Nobel, Fears AI

ANKARA, TURKIYE - OCTOBER 8: An infographic titled "2024 Nobel Prize" created in Ankara, Turkiye on October 8, 2024. 2024 Nobel Prize in physics awarded to John J. Hopfield, Geoffrey E. Hinton for ...
The Conversation

Physics Nobel awarded to neural network pioneers who laid foundations for AI

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
Semiconductor Engineering

Physics Simulation With Graph Neural Networks Targeting Mobile

The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...
EurekAlert!

Integrating physics and AI: Novel graph neural network models enhance precipitation forecasting

In the AI era, pure data-driven meteorological and climate models are gradually catching up with, and even surpassing, traditional numerical models. However, significant challenges persist in current ...
Wired

A Novel Type of Neural Network Comes to the Aid of Big Physics

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...
Physics World

Neural simulation-based inference techniques at the LHC

A neural network is a machine learning model originally inspired by how the human brain works (Courtesy: Shutterstock/Jackie Niam) Precision measurements of theoretical parameters are a core element ...
Quanta Magazine

Sparse Networks Come to the Aid of Big Physics

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...