414 citations
- University of California, Santa CruzUS13 papers
- Western Norway University of Applied SciencesNO12 papers
- Lawrence Livermore National LaboratoryUS8 papers
- Stanford UniversityUS8 papers
- Indian Institute of Technology JammuIN7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- University of VirginiaUS6 papers
- Imperial College LondonGB5 papers
- The University of Texas at AustinUS5 papers
- University of MichiganUS5 papers
- American UniversityUS4 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR4 papers
8 papers · 1 filter
Model Interpretation and Explainability: Towards Creating Transparency in Prediction Models
Donald Kridel, Jacob Dineen, Daniel Dolk +1
Explainable AI (XAI) has a counterpart in analytical modeling which we refer to as model explainability. We tackle the issue of model explainability in the context of prediction mo…
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…
Scaling Artificial Intelligence for Digital Wargaming in Support of Decision-Making
Scotty Black, Christian Darken
In this unprecedented era of technology-driven transformation, it becomes more critical than ever that we aggressively invest in developing robust artificial intelligence (AI) for…
Solving reward-collecting problems with UAVs: a comparison of online optimization and Q-learning
Yixuan Liu, Chrysafis Vogiatzis, Ruriko Yoshida +1
Uncrewed autonomous vehicles (UAVs) have made significant contributions to reconnaissance and surveillance missions in past US military campaigns. As the prevalence of UAVs increas…