Matthew Cleaveland

According to our database, Matthew Cleaveland authored at least 15 papers between 2020 and 2024.

Collaborative distances:

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

2024

Conformal Prediction Regions for Time Series Using Linear Complementarity Programming.

Matthew Cleaveland, Insup Lee, George J. Pappas, Lars Lindemann

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Safe Planning in Dynamic Environments Using Conformal Prediction.

Lars Lindemann, Matthew Cleaveland, Gihyun Shim, George J. Pappas

IEEE Robotics Autom. Lett., 2023

Multi-Modal Conformal Prediction Regions by Optimizing Convex Shape Templates.

Renukanandan Tumu, Matthew Cleaveland, Rahul Mangharam, George J. Pappas, Lars Lindemann

CoRR, 2023

Repairing Learning-Enabled Controllers While Preserving What Works.

Pengyuan Lu, Matthew Cleaveland, Oleg Sokolsky, Insup Lee, Ivan Ruchkin

CoRR, 2023

Distributionally Robust Statistical Verification with Imprecise Neural Networks.

Souradeep Dutta, Michele Caprio, Vivian Lin, Matthew Cleaveland, Kuk Jin Jang, Ivan Ruchkin, Oleg Sokolsky, Insup Lee

CoRR, 2023

Conservative Safety Monitors of Stochastic Dynamical Systems.

Matthew Cleaveland, Oleg Sokolsky, Insup Lee, Ivan Ruchkin

Proceedings of the NASA Formal Methods - 15th International Symposium, 2023

Adaptive Conformal Prediction for Motion Planning among Dynamic Agents.

Anushri Dixit, Lars Lindemann, Skylar X. Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick

Proceedings of the Learning for Dynamics and Control Conference, 2023

Causal Repair of Learning-Enabled Cyber-Physical Systems.

Pengyuan Lu, Ivan Ruchkin, Matthew Cleaveland, Oleg Sokolsky, Insup Lee

Proceedings of the IEEE International Conference on Assured Autonomy, 2023

2022

Risk verification of stochastic systems with neural network controllers.

Matthew Cleaveland, Lars Lindemann, Radoslav Ivanov, George J. Pappas

Artif. Intell., 2022

Learning Enabled Fast Planning and Control in Dynamic Environments with Intermittent Information.

Matthew Cleaveland, Esen Yel, Yiannis Kantaros, Insup Lee, Nicola Bezzo

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Confidence Composition for Monitors of Verification Assumptions.

Ivan Ruchkin, Matthew Cleaveland, Radoslav Ivanov, Pengyuan Lu, Taylor J. Carpenter, Oleg Sokolsky, Insup Lee

Proceedings of the 13th ACM/IEEE International Conference on Cyber-Physical Systems, 2022

Monotonic Safety for Scalable and Data-Efficient Probabilistic Safety Analysis.

Matthew Cleaveland, Ivan Ruchkin, Oleg Sokolsky, Insup Lee

Proceedings of the 13th ACM/IEEE International Conference on Cyber-Physical Systems, 2022

2021

Robust Motion Planning in the Presence of Estimation Uncertainty.

Lars Lindemann, Matthew Cleaveland, Yiannis Kantaros, George J. Pappas

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Confidence Monitoring and Composition for Dynamic Assurance of Learning-Enabled Autonomous Systems - Position Paper.

Ivan Ruchkin, Matthew Cleaveland, Oleg Sokolsky, Insup Lee

Proceedings of the Formal Methods in Outer Space, 2021

2020

Assurance Case Patterns for Cyber-Physical Systems with Deep Neural Networks.

Ramneet Kaur, Radoslav Ivanov, Matthew Cleaveland, Oleg Sokolsky, Insup Lee

Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops, 2020