Abstract: Two-dimensional (2D) convolution is a fundamental operation widely employed in various fields such as image processing, computer vision, and medical imaging. Its capacity to extract ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to four-digit multiplication, a task taught in ...

This repository contains the reference software and hardware artifacts for the paper FANE: FPGA-based FP8 Approximate Neural Network Engine. The project is organized around two complementary parts: sw ...

Hi, thank you for sharing the code. Regarding the Interactive Convolution Block, it is written in the paper: ``The element-wise multiplication encourages interactions between features extracted at ...

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...

Camilla Gilmore receives funding from the Economic and Social Research Council. Lucy Cragg receives funding from the Economic and Social Research Council. Natasha Guy does not work for, consult, own ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...