Adam J. Thorpe

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 25

Top Topics

Prior Domain Knowledge

Top Venues

Publications

Tyler Ingebrand, Adam J. Thorpe, Ufuk Topcu
Zero-Shot Transfer of Neural ODEs. CoRR (2024)
Kevin S. Miller, Adam J. Thorpe, Ufuk Topcu
Active Learning of Dynamics Using Prior Domain Knowledge in the Sampling Process. CoRR (2024)
Harini Sridhar, Gaojian Huang, Adam J. Thorpe, Meeko Oishi, Brandon J. Pitts
Characterizing the Effect of Mind Wandering on Braking Dynamics in Partially Autonomous Vehicles. ACM Trans. Cyber Phys. Syst. 8 (3) (2024)
Adam J. Thorpe, Cyrus Neary, Franck Djeumou, Meeko M. K. Oishi, Ufuk Topcu
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control. CoRR (2023)
Adam J. Thorpe
Refining Human-Centered Autonomy Using Side Information. CoRR (2023)
Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi
Data-Driven Stochastic Optimal Control Using Kernel Gradients. ACC (2023)
Adam J. Thorpe, Thomas Lew, Meeko M. K. Oishi, Marco Pavone
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. CoRR (2022)
Adam J. Thorpe, Thomas Lew, Meeko Oishi, Marco Pavone
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. L4DC (2022)
Kendric R. Ortiz, Adam J. Thorpe, AnaMaria Perez, Maya Luster, Brandon J. Pitts, Meeko Oishi
Characterizing Within-Driver Variability in Driving Dynamics During Obstacle Avoidance Maneuvers. CoRR (2022)
Adam J. Thorpe, Meeko M. K. Oishi
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. CoRR (2022)
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi
State-based confidence bounds for data-driven stochastic reachability using Hilbert space embeddings. Autom. 138 (2022)
Abraham P. Vinod, Adam J. Thorpe, Philip A. Olaniyi, Tyler H. Summers, Meeko M. K. Oishi
Sensor Selection for Dynamics-Driven User-Interface Design. IEEE Trans. Control. Syst. Technol. 30 (1) (2022)
Adam J. Thorpe, Meeko Oishi
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. HSCC (2022)
Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi
Data-Driven Stochastic Optimal Control Using Kernel Gradients. CoRR (2022)
Adam J. Thorpe, Meeko M. K. Oishi
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CoRR (2021)
Adam J. Thorpe, Meeko M. K. Oishi
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CDC (2021)
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi
SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. CDC (2021)
Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi
Approximate Stochastic Reachability for High Dimensional Systems. ACC (2021)
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi
Learning Approximate Forward Reachable Sets Using Separating Kernels. L4DC (2021)
Adam J. Thorpe, Meeko M. K. Oishi
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. IEEE Control. Syst. Lett. 4 (2) (2020)
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi
Data-Driven Stochastic Reachability Using Hilbert Space Embeddings. CoRR (2020)
Abraham P. Vinod, Adam J. Thorpe, Philip A. Olaniyi, Tyler H. Summers, Meeko M. K. Oishi
Trust-based user-interface design for human-automation systems. CoRR (2020)
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi
SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. CoRR (2020)
Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi
Stochastic Reachability for Systems up to a Million Dimensions. CoRR (2019)
Adam J. Thorpe, Meeko M. K. Oishi
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. CoRR (2019)