Learning Systems

Highlights

Coefficient of variation (CoV) and total fuel injected results for the best spiking neural networks for each generation of evolution for all ten runs for the engine simulator. The best network is defined as the network with the lowest fuel injected that is also below the CoV threshold of 3 percent (averaged over ten test runs).

Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency

spiking neural network generated by EONS using the Caspian platform CDA ORNL

Caspian: A Neuromorphic Development Platform

Visual Analytics System Overview: The system consists of three different views: a lineage view (1), a fitness-parameter view (2), and a network architecture view (3). CDA ORNL

Visualization System for Evolutionary Neural Networks for Deep Learning

The Iterated Local Model For Social Networks

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Summary of Bayesian-based Hyperparameter Optimization Results: a. Grid search: Whetstone accuracy for 256 different HP sets. b. Bayesian-based HP optimization: selected 15 HP combinations to find optimal hyperparameter set (shown with red star). c. Bayesian-based HP optimization result for four state-of-the-art datasets

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

EONS algorithm overview ORNL CDA Computer Data Analytics

Evolutionary Optimization for Neuromorphic Systems

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems - CDA ORNL

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems

Left - Memristive neuromorphic system Right - Spiking neural network designed by EONS

Automated Design of Neuromorphic Networks for Scientific Applications at the Edge

Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems

Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems

Evolving Energy Efficient Convolutional Neural Networks

Evolving Energy Efficient Convolutional Neural Networks

Exploring flexible communications for streamlining DNN ensemble training pipelines