10 citations · 18 across the 4 of their papers we have counts for
4 papers · 1 filter
Swarm Characteristic Classification using Robust Neural Networks with Optimized Controllable Inputs
Donald W. Peltier, Isaac Kaminer, Abram Clark +1
Having the ability to infer characteristics of autonomous agents would profoundly revolutionize defense, security, and civil applications. Our previous work was the first to demons…
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models
John Fischer, Marko Orescanin, Justin Loomis +1
Federated learning (FL) is an approach to training machine learning models that takes advantage of multiple distributed datasets while maintaining data privacy and reducing communi…
Swarm Characteristics Classification Using Neural Networks
Donald W. Peltier, Isaac Kaminer, Abram Clark +1
Understanding the characteristics of swarming autonomous agents is critical for defense and security applications. This article presents a study on using supervised neural network…
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition
John Fischer, Marko Orescanin, Eric Eckstrand
Transfer learning (TL) is an increasingly popular approach to training deep learning (DL) models that leverages the knowledge gained by training a foundation model on diverse, larg…