This library provides a self-contained and easy to use implementation of matrix container class. The main features include: Full template parameterization with support for both real and complex ...

Neurophos is taking a crack at solving the AI industry's power efficiency problem with an optical chip that uses a composite material to do the math required in AI inferencing tasks.

Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...

Abstract: Sparse matrices have recently played a significant and impactful role in scientific computing, including artificial intelligence-related fields. According to historical studies on sparse ...

AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime ...

Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...