This repository contains working examples of Neural Network Libraries. Before running any of the examples in this repository, you must install the Python package for Neural Network Libraries. The ...

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 ...

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to ...

In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network ...

Abstract: In recent years, numerous designs have used systolic arrays to accelerate convolutional neural network (CNN) inference. In this work, we demonstrate that we can further speed up CNN ...

Project implementation for Machine Learning exam, Master's Degree Course in Computer Science, Artificial Intelligence curriculum, University of Pisa. Professor: Alessio Micheli. For more further info ...

Despite over 300 y of effort, no solutions exist for predicting when a general planetary configuration will become unstable. We introduce a deep learning architecture to push forward this problem for ...