Mrs: High Performance MapReduce for Iterative and Asynchronous Algorithms in Python. - Jeffrey Lund; Chace Ashcraft; Andrew W. McNabb; Kevin D. Seppi (PyHPC@SC, 2016)

Human-Swarm Interaction as Shared Control: Achieving Flexible Fault-Tolerant Systems. - Jacob W. Crandall; Nathan Anderson; Chace Ashcraft; John R. Grosh; Jonah Henderson; Joshua McClellan; Aadesh Neupane; Michael A. Goodrich (HCI (5), 2017)

Moderating Operator Influence in Human-Swarm Systems. - Chace Ashcraft; Michael A. Goodrich; Jacob W. Crandall (SMC, 2019)

The TrojAI Software Framework: An OpenSource tool for Embedding Trojans into Deep Learning Models. - Kiran Karra; Chace Ashcraft; Neil Fendley (CoRR, 2020)

PICO: Primitive Imitation for COntrol. - Corban G. Rivera; Katie M. Popek; Chace Ashcraft; Edward W. Staley; Kapil D. Katyal; Bart L. Paulhamus (CoRR, 2020)

Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers. - Chace Ashcraft; Kiran Karra (CoRR, 2021)

SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks. - Kiran Karra; Chace Ashcraft (CoRR, 2021)

Machine Learning aided Crop Yield Optimization. - Chace Ashcraft; Kiran Karra (CoRR, 2021)

Meta Arcade: A Configurable Environment Suite for Meta-Learning. - Edward W. Staley; Chace Ashcraft; Benjamin Stoler; Jared Markowitz; Gautam K. Vallabha; Christopher Ratto; Kapil D. Katyal (CoRR, 2021)

SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks. - Kiran Karra; Chace Ashcraft; Cash Costello (DASC/PiCom/CBDCom/CyberSciTech, 2022)

L2Explorer: A Lifelong Reinforcement Learning Assessment Environment. - Erik C. Johnson; Eric Q. Nguyen; Blake Schreurs; Chigozie S. Ewulum; Chace Ashcraft; Neil M. Fendley; Megan M. Baker; Alexander New; Gautam K. Vallabha (CoRR, 2022)

Structural Similarity for Improved Transfer in Reinforcement Learning. - Chace Ashcraft; Benjamin Stoler; Chigozie S. Ewulum; Susama Agarwala (CoRR, 2022)

Latent Properties of Lifelong Learning Systems. - Corban G. Rivera; Chace Ashcraft; Alexander New; James Schmidt; Gautam K. Vallabha (CoRR, 2022)

Context-Adaptive Deep Neural Networks via Bridge-Mode Connectivity. - Nathan Drenkow; Alvin Tan; Chace Ashcraft; Kiran Karra (CoRR, 2022)

Learning generalizable behaviors from demonstration. - Corban G. Rivera; Katie M. Popek; Chace Ashcraft; Edward W. Staley; Kapil D. Katyal; Bart L. Paulhamus (Frontiers Neurorobotics, 2022)

Using Artificial Intelligence to aid Scientific Discovery of Climate Tipping Points. - Jennifer Sleeman; David Chung; Chace Ashcraft; Jay Brett; Anand Gnanadesikan; Yannis G. Kevrekidis; Marisa Hughes; Thomas W. N. Haine; Marie-Aude Pradal; Renske Gelderloos; Caroline Tang; Anshu Saksena; et al. (CoRR, 2023)

A Generative Adversarial Network for Climate Tipping Point Discovery (TIP-GAN). - Jennifer Sleeman; David Chung; Anand Gnanadesikan; Jay Brett; Yannis G. Kevrekidis; Marisa Hughes; Thomas W. N. Haine; Marie-Aude Pradal; Renske Gelderloos; Chace Ashcraft; Caroline Tang; Anshu Saksena; et al. (CoRR, 2023)

Neuro-Symbolic Bi-Directional Translation - Deep Learning Explainability for Climate Tipping Point Research. - Chace Ashcraft; Jennifer Sleeman; Caroline Tang; Jay Brett; Anand Gnanadesikan (CoRR, 2023)

Difference Learning for Air Quality Forecasting Transport Emulation. - Reed River Chen; Christopher Ribaudo; Jennifer Sleeman; Chace Ashcraft; Collin Kofroth; Marisa Hughes; Ivanka Stajner; Kevin Viner; Kai Wang (CoRR, 2024)

Investigating the Treacherous Turn in Deep Reinforcement Learning. - Chace Ashcraft; Kiran Karra; Josh Carney; Nathan Drenkow (CoRR, 2025)

Backdoors in DRL: Four Environments Focusing on In-distribution Triggers. - Chace Ashcraft; Ted Staley; Josh Carney; Cameron Hickert; Kiran Karra; Nathan Drenkow (CoRR, 2025)

Large Language Models are Highly Aligned with Human Ratings of Emotional Stimuli. - Mattson Ogg; Chace Ashcraft; Ritwik Bose; Raphael Norman-Tenazas; Michael Wolmetz (CoRR, 2025)