Human-swarm interaction as shared control: Achieving flexible fault-tolerant systems JW Crandall, N Anderson, C Ashcraft, J Grosh, J Henderson, J McClellan, ... Engineering Psychology and Cognitive Ergonomics: Performance, Emotion and …, 2017 | 28 | 2017 |
The trojai software framework: An opensource tool for embedding trojans into deep learning models K Karra, C Ashcraft, N Fendley arXiv preprint arXiv:2003.07233, 2020 | 27 | 2020 |
Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers C Ashcraft, K Karra arXiv preprint arXiv:2106.07798, 2021 | 21 | 2021 |
Moderating operator influence in human-swarm systems CC Ashcraft, MA Goodrich, JW Crandall 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC …, 2019 | 13 | 2019 |
Machine Learning aided Crop Yield Optimization C Ashcraft, K Karra arXiv preprint arXiv:2111.00963, 2021 | 12 | 2021 |
L2Explorer: A Lifelong Reinforcement Learning Assessment Environment EC Johnson, EQ Nguyen, B Schreurs, CS Ewulum, C Ashcraft, ... arXiv preprint arXiv:2203.07454, 2022 | 11 | 2022 |
Meta Arcade: A Configurable Environment Suite for Meta-Learning EW Staley, C Ashcraft, B Stoler, J Markowitz, G Vallabha, C Ratto, ... arXiv preprint arXiv:2112.00583, 2021 | 5 | 2021 |
A Generative Adversarial Network for Climate Tipping Point Discovery (TIP-GAN) J Sleeman, D Chung, A Gnanadesikan, J Brett, Y Kevrekidis, M Hughes, ... arXiv preprint arXiv:2302.10274, 2023 | 4 | 2023 |
Using Artificial Intelligence to aid Scientific Discovery of Climate Tipping Points J Sleeman, D Chung, C Ashcraft, J Brett, A Gnanadesikan, Y Kevrekidis, ... arXiv preprint arXiv:2302.06852, 2023 | 3 | 2023 |
Machine learning for activity-based road transportation emissions estimation D Rollend, K Foster, TM Kott, R Mocharla, R Muñoz, N Fendley, ... Environmental Data Science 2, e38, 2023 | 2 | 2023 |
Structural Similarity for Improved Transfer in Reinforcement Learning CC Ashcraft, B Stoler, C Ewulum, S Agarwala arXiv preprint arXiv:2207.13813, 2022 | 2 | 2022 |
Meta Arcade: A Configurable Environment Suite for Deep Reinforcement Learning and Meta-Learning EW Staley, C Ashcraft, B Stoler, J Markowitz, G Vallabha, C Ratto, ... Deep RL Workshop NeurIPS 2021, 2021 | 2 | 2021 |
Verification and Validation of a Coordinate-Transformation Method in Axisymmetric Transient Magnetics CC Ashcraft, JHJ Niederhaus, AC Robinson Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016 | 2 | 2016 |
Artificial Intelligence Air Quality Forecast Emulation of Atmospheric Tracers J Sleeman, I Stajner, CA Keller, C Ashcraft, R Montuoro, M Halem, ... 103rd AMS Annual Meeting, 2023 | 1 | 2023 |
Using Deep Learning for Climate Tipping Point Discovery to Understand Atlantic Meridional Overturning Circulation (AMOC) Collapse JA Sleeman, D Chung, C Ashcraft, A Saksena, GJ Brett, M Hughes, ... AGU Fall Meeting Abstracts 2022, OS36A-08, 2022 | 1 | 2022 |
Learning generalizable behaviors from demonstration. C Rivera, KM Popek, C Ashcraft, EW Staley, KD Katyal, BL Paulhamus Frontiers in Neurorobotics 16, 932652-932652, 2022 | 1 | 2022 |
Learning generalizable behaviors from demonstration C Rivera, KM Popek, C Ashcraft, EW Staley, KD Katyal, BL Paulhamus Frontiers in Neurorobotics 16, 932652, 2022 | 1 | 2022 |
Moderating Influence as a Design Principle for Human-Swarm Interaction CC Ashcraft Brigham Young University, 2019 | 1 | 2019 |
Mrs: high performance mapreduce for iterative and asynchronous algorithms in python J Lund, C Ashcraft, A McNabb, K Seppi 2016 6th Workshop on Python for High-Performance and Scientific Computing …, 2016 | 1 | 2016 |
Adversarial Machine Learning and the Future Hybrid Battlespace C Ratto, M Pekala, N Fendley, N Drenkow, K Karra, C Ashcraft, C Costello, ... The Johns Hopkins University Applied Physics Laboratory, 0 | 1 | |