4 citations · 9 across the 6 of their papers we have counts for
7 papers
Proceedings of the Robust Artificial Intelligence System Assurance (RAISA) Workshop 2022
Olivia Brown, Brad Dillman
The Robust Artificial Intelligence System Assurance (RAISA) workshop will focus on research, development and application of robust artificial intelligence (AI) and machine learning…
Tools and Practices for Responsible AI Engineering
Ryan Soklaski, Justin Goodwin, Olivia Brown +2
Responsible Artificial Intelligence (AI) - the practice of developing, evaluating, and maintaining accurate AI systems that also exhibit essential properties such as robustness and…
Principles for Evaluation of AI/ML Model Performance and Robustness
Olivia Brown, Andrew Curtis, Justin Goodwin
The Department of Defense (DoD) has significantly increased its investment in the design, evaluation, and deployment of Artificial Intelligence and Machine Learning (AI/ML) capabil…
Fast Training of Deep Neural Networks Robust to Adversarial Perturbations
Justin Goodwin, Olivia Brown, Victoria Helus
Deep neural networks are capable of training fast and generalizing well within many domains. Despite their promising performance, deep networks have shown sensitivities to perturba…
Safe Predictors for Enforcing Input-Output Specifications
Stephen Mell, Olivia Brown, Justin Goodwin +1
We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-out…
Kernelized Capsule Networks
Taylor Killian, Justin Goodwin, Olivia Brown +1
Capsule Networks attempt to represent patterns in images in a way that preserves hierarchical spatial relationships. Additionally, research has demonstrated that these techniques m…
Learning Robust Representations for Automatic Target Recognition
Justin A. Goodwin, Olivia M. Brown, Taylor W. Killian +1
Radio frequency (RF) sensors are used alongside other sensing modalities to provide rich representations of the world. Given the high variability of complex-valued target responses…