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Adam J. Thorpe
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2020 – today
- 2024
- [i14]Kevin S. Miller
, Adam J. Thorpe, Ufuk Topcu:
Active Learning of Dynamics Using Prior Domain Knowledge in the Sampling Process. CoRR abs/2403.17233 (2024) - [i13]Tyler Ingebrand, Adam J. Thorpe, Ufuk Topcu:
Zero-Shot Transfer of Neural ODEs. CoRR abs/2405.08954 (2024) - 2023
- [c7]Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi:
Data-Driven Stochastic Optimal Control Using Kernel Gradients. ACC 2023: 2548-2553 - [i12]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 abs/2301.03565 (2023) - [i11]Adam J. Thorpe:
Refining Human-Centered Autonomy Using Side Information. CoRR abs/2305.05607 (2023) - 2022
- [j3]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: 110146 (2022) - [j2]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): 71-84 (2022) - [c6]Adam J. Thorpe, Meeko Oishi
:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. HSCC 2022: 21:1-21:12 - [c5]Adam J. Thorpe, Thomas Lew, Meeko Oishi, Marco Pavone:
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. L4DC 2022: 790-802 - [i10]Adam J. Thorpe, Thomas Lew, Meeko M. K. Oishi, Marco Pavone:
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. CoRR abs/2202.04193 (2022) - [i9]Adam J. Thorpe, Meeko M. K. Oishi:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. CoRR abs/2203.06290 (2022) - [i8]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 abs/2206.01331 (2022) - [i7]Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi:
Data-Driven Stochastic Optimal Control Using Kernel Gradients. CoRR abs/2209.09205 (2022) - 2021
- [c4]Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi
:
Approximate Stochastic Reachability for High Dimensional Systems. ACC 2021: 1287-1293 - [c3]Adam J. Thorpe, Meeko M. K. Oishi
:
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CDC 2021: 904-911 - [c2]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: 5073-5079 - [c1]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
Learning Approximate Forward Reachable Sets Using Separating Kernels. L4DC 2021: 201-212 - [i6]Adam J. Thorpe, Meeko M. K. Oishi:
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CoRR abs/2103.12759 (2021) - 2020
- [j1]Adam J. Thorpe
, Meeko M. K. Oishi
:
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. IEEE Control. Syst. Lett. 4(2): 512-517 (2020) - [i5]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 abs/2004.07176 (2020) - [i4]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
Data-Driven Stochastic Reachability Using Hilbert Space Embeddings. CoRR abs/2010.08036 (2020) - [i3]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. CoRR abs/2011.10610 (2020)
2010 – 2019
- 2019
- [i2]Adam J. Thorpe
, Meeko M. K. Oishi:
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. CoRR abs/1908.00697 (2019) - [i1]Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Stochastic Reachability for Systems up to a Million Dimensions. CoRR abs/1910.10818 (2019)
Coauthor Index
aka: Meeko Oishi
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last updated on 2024-08-05 21:14 CEST by the dblp team
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