Single neurons in mouse sensorimotor cortex are organized by their activity features into distinct subpopulations with area-spanning footprints whose boundaries align closely with anatomical and ...

📖 Start here: 5-minute introduction page — hero, install, five runnable snippets covering simulation → fitting → KS goodness-of-fit → decoding → SSGLM, plus a paper-example thumbnail gallery and v1.4 ...

A distinguishing feature of the neural network models used in Physics and Chemistry is that they must obey basic underlying symmetries, such as symmetry to translations, rotations, and the exchange of ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Natural physical systems evolve with certain global quantities being minimized or maximized due to physical laws. For example, charges in conductors redistribute to reach electrostatic equilibrium, ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

We present a machine learning method based on random projections with Johnson-Lindenstrauss (JL) and/or Rahimi and Recht (2007) Random Fourier Features (RFFN) for efficiently learning linear and ...

The state extended its current personal privacy law to include the neural data increasingly coveted by technology companies. By Jonathan Moens On Saturday, Governor Gavin Newsom of California signed a ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...