This valuable study provides a practical computational framework for inferring latent neural states directly from calcium fluorescence recordings, bypassing the traditional need for a separate spike ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Forbes contributors publish independent expert analyses and insights. Philip Maymin, a professor of analytics and AI, covers finance and AI. Is this a deep learning neural network, with blue inputs, ...

Will computers ever match or surpass human-level intelligence — and, if so, how? When the Association for the Advancement of Artificial Intelligence (AAAI), based in Washington DC, asked its members ...

Calling the model on the input returns a 2-dimensional tensor with dim=0 corresponding to each output of 10 raw predicted values for each class, and dim=1 corresponding to the individual values of ...

In a recent review published in the journal Current Biology, researchers examined the origins, mechanisms, and significance of interoception (the sensing and processing of internal bodily states) and ...

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 ...

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 ...

With work on machine learning that uses artificial neural networks, John J. Hopfield and Geoffrey E. Hinton “showed a completely new way for us to use computers,” the committee said. By Derrick Bryson ...