Fast convolution algorithms with Python types. A module for performing repeated convolutions involving high-level Python objects (which includes large integers, rationals, SymPy terms, Sage objects, ...

A Python module to generate fast bilinear algorithms for different variants of convolution. We provide a simple function to generate Toom-Cook algorithms with either integer nodes (cheby=False) or ...

The convolution operation is a data-intensive algorithm that requires a lot of computing power. As convolutional neural networks become more complex, there are limitations to algorithmically ...

In out‐of‐hospital cardiac arrest, an algorithm within an automated external defibrillator is the major determinant to deliver defibrillation. This study developed and validated the performance of a ...

Convolution is the most time-consuming operation in modern deep artificial neural networks, so its performance is crucial for fast inference. One of the standard approaches to fast convolution ...