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2020 – today
- 2021
[i5]Jeff Druce, Michael Harradon, James Tittle:
Explainable Artificial Intelligence (XAI) for Increasing User Trust in Deep Reinforcement Learning Driven Autonomous Systems. CoRR abs/2106.03775 (2021)- [i4]Jeff Druce, James Niehaus, Vanessa Moody, David D. Jensen, Michael L. Littman:
Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program. CoRR abs/2106.05506 (2021) - 2020
- [i3]Shashank Manjunath, Aitzaz Nathaniel, Jeff Druce, Stan German:
Improving the Performance of Fine-Grain Image Classifiers via Generative Data Augmentation. CoRR abs/2008.05381 (2020)
2010 – 2019
- 2019
- [i2]Daniel Takabi, Robert Podschwadt, Jeff Druce, Curt Wu, Kevin Procopio:
Privacy preserving Neural Network Inference on Encrypted Data with GPUs. CoRR abs/1911.11377 (2019) - 2018
- [c2]Jeff Druce, Max Metzger, Nidhi Gupta, Rishi Kundi:
Predicting observable and occult injuries in trauma patients from sparse measurements. AIH@IJCAI 2018: 65-69 - [i1]Michael Harradon, Jeff Druce, Brian E. Ruttenberg:
Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations. CoRR abs/1802.00541 (2018) - 2017
- [c1]Brian E. Ruttenberg, Dave Blumstein, Jeff Druce, Michael Howard, Fred Reed, Leslie Wilfong, Crystal Lister, Steve Gaskin, Meaghan Foley, Daniel Scofield:
Probabilistic Modeling of Insider Threat Detection Systems. GraMSec@CSF 2017: 91-98
Coauthor Index
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