research
∙
06/16/2023
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation
Recently, machine learning systems have gained prominence in real-time, ...
share
research
∙
05/16/2023
One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection
Neural networks (NNs) are capable of learning complex patterns and relat...
research
∙
03/14/2023
Model-to-Circuit Cross-Approximation For Printed Machine Learning Classifiers
Printed electronics (PE) promises on-demand fabrication, low non-recurri...
research
∙
02/28/2023
Co-Design of Approximate Multilayer Perceptron for Ultra-Resource Constrained Printed Circuits
Printed Electronics (PE) exhibits on-demand, extremely low-cost hardware...
research
∙
01/26/2023
Hardware-Aware Automated Neural Minimization for Printed Multilayer Perceptrons
The demand of many application domains for flexibility, stretchability, ...
research
∙
10/02/2022
Approximate Computing and the Efficient Machine Learning Expedition
Approximate computing (AxC) has been long accepted as a design alternati...
research
∙
03/15/2022
Approximate Decision Trees For Machine Learning Classification on Tiny Printed Circuits
Although Printed Electronics (PE) cannot compete with silicon-based syst...
research
∙
03/11/2022
