1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Architectural Implications of Embedding Dimension during GCN on CPU and GPU
Matthew Adiletta, David Brooks, Gu-Yeon Wei
Graph Neural Networks (GNNs) are a class of neural networks designed to extract information from the graphical structure of data. Graph Convolutional Networks (GCNs) are a widely u…
cs.AR2020
Optimization Techniques to Improve Inference Performance of a Forward Propagating Neural Network on an FPGA
Matthew Joseph Adiletta, Brian Flanagan
This paper describes an optimized implementation of a Forward Propagating Classification Neural Network which has been previously trained. The implementation described highlights a…
cs.MM2020
An Artistic Visualization of Music Modeling a Synesthetic Experience
Matthew Joseph Adiletta, Oliver Thomas
This project brings music to sight. Music can be a visual masterpiece. Some people naturally experience a visualization of audio - a condition called synesthesia. The type of synes…