1 citations · 1 across the 3 of their papers we have counts for
3 papers
Improvements in Interlayer Pipelining of CNN Accelerators Using Genetic Algorithms
Mark Horeni, Siddharth Joshi
Deploying Convolutional Neural Networks (CNNs) on edge platforms necessitates efficient hardware acceleration. Any unnecessary data movement in such accelerators can unacceptably d…
Hadamard Domain Training with Integers for Class Incremental Quantized Learning
Martin Schiemer, Clemens JS Schaefer, Jayden Parker Vap +4
Continual learning is a desirable feature in many modern machine learning applications, which allows in-field adaptation and updating, ranging from accommodating distribution shift…
The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks
Clemens JS Schaefer, Pooria Taheri, Mark Horeni +1
Energy efficient implementations and deployments of Spiking neural networks (SNNs) have been of great interest due to the possibility of developing artificial systems that can achi…