Chace Ashcraft

According to our database, Chace Ashcraft authored at least 19 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

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

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, Larry White

CoRR, 2023

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, Larry White

CoRR, 2023

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, September, 2022

Context-Adaptive Deep Neural Networks via Bridge-Mode Connectivity.

Nathan Drenkow, Alvin Tan, Chace Ashcraft, Kiran Karra

CoRR, 2022

Latent Properties of Lifelong Learning Systems.

Corban G. Rivera, Chace Ashcraft, Alexander New, James Schmidt, Gautam K. Vallabha

CoRR, 2022

Structural Similarity for Improved Transfer in Reinforcement Learning.

Chace Ashcraft, Benjamin Stoler, Chigozie S. Ewulum, Susama Agarwala

CoRR, 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

SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks.

Kiran Karra, Chace Ashcraft, Cash Costello

Proceedings of the IEEE Intl. Conf. on Dependable, 2022

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

Machine Learning aided Crop Yield Optimization.

Chace Ashcraft, Kiran Karra

CoRR, 2021

SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks.

Kiran Karra, Chace Ashcraft

CoRR, 2021

Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers.

Chace Ashcraft, Kiran Karra

CoRR, 2021

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

The TrojAI Software Framework: An OpenSource tool for Embedding Trojans into Deep Learning Models.

Kiran Karra, Chace Ashcraft, Neil Fendley

CoRR, 2020

2019

Moderating Operator Influence in Human-Swarm Systems.

Chace Ashcraft, Michael A. Goodrich, Jacob W. Crandall

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2017

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

Proceedings of the Engineering Psychology and Cognitive Ergonomics: Performance, Emotion and Situation Awareness, 2017

2016

Mrs: High Performance MapReduce for Iterative and Asynchronous Algorithms in Python.

Jeffrey Lund, Chace Ashcraft, Andrew W. McNabb, Kevin D. Seppi

Proceedings of the 6th Workshop on Python for High-Performance and Scientific Computing, 2016