The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...

Smooth developer experience is fundamental in artificial intelligence designs. Development toolkits can streamline the preparation of trained neural networks for edge and low-latency data-center ...

Inferred movements — New research from the University of Edinburgh and Adobe Research could be a huge leap forward in allowing creating more natural in-game movements. The research uses deep neural ...

Assistant Professor of Electrical and Computer Engineering Jason Eshraghian. Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial ...

Dr. James McCaffrey of Microsoft Research uses a full-code, step-by-step demo to show how to predict the annual income of a person based on their sex, age, state where they live and political leaning.

If you would like to learn more about building your very own neural networks or machine learning you may be interested in a free course has been made available by the team over at freeCodeCamp.org.

An open source code library for brain-inspired deep learning, called 'snnTorch,' has surpassed 100,000 downloads and is used in a wide variety of projects. A new paper details the code and offers a ...

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...