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ORCIDAdam J. Thorpe
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2020 – today
- 2024
[j4]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): 26:1-26:21 (2024)- [c10]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. ACC 2024: 3130-3137 - [c9]Madeleine Yuh, Ethan Rabb, Adam J. Thorpe, Neera Jain:
Using Reward Shaping to Train Cognitive-Based Control Policies for Intelligent Tutoring Systems. ACC 2024: 3223-3230 - [i17]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) - [i16]Tyler Ingebrand, Adam J. Thorpe, Ufuk Topcu:
Zero-Shot Transfer of Neural ODEs. CoRR abs/2405.08954 (2024) - [i15]Hamzah Khan, Adam J. Thorpe, David Fridovich-Keil:
Act Natural! Projecting Autonomous System Trajectories Into Naturalistic Behavior Sets. CoRR abs/2405.19292 (2024) - [i14]Tyler Ingebrand, Adam J. Thorpe, Somdatta Goswami, Krishna Kumar, Ufuk Topcu:
Basis-to-Basis Operator Learning Using Function Encoders. CoRR abs/2410.00171 (2024) - 2023
- [c8]Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi:
Data-Driven Stochastic Optimal Control Using Kernel Gradients. ACC 2023: 2548-2553 - [i13]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) - [i12]Adam J. Thorpe:
Refining Human-Centered Autonomy Using Side Information. CoRR abs/2305.05607 (2023) - [i11]Junette Hsin, Shubhankar Agarwal, Adam J. Thorpe, David Fridovich-Keil:
GPSINDy: Data-Driven Discovery of Equations of Motion. CoRR abs/2309.11076 (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) - [c7]Adam J. Thorpe, Meeko Oishi:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. HSCC 2022: 21:1-21:12 - [c6]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
- [c5]Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Approximate Stochastic Reachability for High Dimensional Systems. ACC 2021: 1287-1293 - [c4]Alessandro Abate, Henk A. P. Blom, Marc Bouissou, Nathalie Cauchi, Hassane Chraibi, Joanna Delicaris, Sofie Haesaert, Arnd Hartmanns, Mahmoud Khaled, Abolfazl Lavaei, Hao Ma, Kaushik Mallik, Mathis Niehage, Anne Remke, Stefan Schupp, Fedor Shmarov, Sadegh Soudjani, Adam J. Thorpe, Vlad Turcuman, Paolo Zuliani:
ARCH-COMP21 Category Report: Stochastic Models. ARCH@ADHS 2021: 55-89 - [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 2024-11-06 21:32 CET by the dblp team
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