Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

In both cases the neural network is translating what it “sees” into numbers and performing maths (specifically, matrix operations) on them. But transformers have their limitations.

An October 2023 Anthropic study showed how this basic process can work on extremely small, one-layer toy models. The company's new paper scales that up immensely, identifying tens of millions of ...

If you can get past the coining of yet another new word to talk about neural network designs, think about this: modeling the actual synapse can be a way to improve digital systems. In other words ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

I trained my quantum-tunnelling neural network to recognise the Necker cube and Rubin’s vase illusions. When faced with the illusion as an input, it produced an output of one or the other of the ...

In this study, we present a deep learning method, named DeepGS, to predict phenotypes from genotypes. Using a deep convolutional neural network, DeepGS uses hidden variables that jointly represent ...