Three new neural network-based tools enable fast, accurate alignment and annotation of images even in very wiggly subjects.

The company open sourced an 8-billion-parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...

Another theory held that the forces between two particles falls off exponentially in direct relationship to the distance between two particles and that the factor by which it drops is not dependent on ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...

I vividly recall that, when I was a graduate student in the late 1990s, on the bookshelves of the professors’ bookcases, I would often see the two volumes of Parallel Distributed Processing: ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

What is CNN in Deep Learning? In this video, we understand what is CNN in Deep Learning and why do we need it. CNN (or Convolutional Neural Network) is the building block of all Computer Vision ...

We present ‘NeuralConstraints,’ a suite of computer-assisted composition tools that integrates a feedforward neural network as a rule within a constraint-based composition framework.