Assurance Case Patterns for Cyber-Physical Systems with Deep Neural Networks. - Ramneet Kaur; Radoslav Ivanov; Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001 (SAFECOMP Workshops, 2020)

Confidence Monitoring and Composition for Dynamic Assurance of Learning-Enabled Autonomous Systems - Position Paper. - Ivan Ruchkin; Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001 (Formal Methods in Outer Space, 2021)

Robust Motion Planning in the Presence of Estimation Uncertainty. - Lars Lindemann; Matthew Cleaveland; Yiannis Kantaros; George J. Pappas (CDC, 2021)

Monotonic Safety for Scalable and Data-Efficient Probabilistic Safety Analysis. - Matthew Cleaveland; Ivan Ruchkin; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2022)

Confidence Composition for Monitors of Verification Assumptions. - Ivan Ruchkin; Matthew Cleaveland; Radoslav Ivanov; Pengyuan Lu; Taylor J. Carpenter; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2022)

Learning Enabled Fast Planning and Control in Dynamic Environments with Intermittent Information. - Matthew Cleaveland; Esen Yel; Yiannis Kantaros; Insup Lee 001; Nicola Bezzo (IROS, 2022)

Risk verification of stochastic systems with neural network controllers. - Matthew Cleaveland; Lars Lindemann; Radoslav Ivanov; George J. Pappas (Artif. Intell., 2022)

Causal Repair of Learning-Enabled Cyber-Physical Systems. - Pengyuan Lu; Ivan Ruchkin; Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001 (ICAA, 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 (L4DC, 2023)

Conservative Safety Monitors of Stochastic Dynamical Systems. - Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001; Ivan Ruchkin (NFM, 2023)

Safe Planning in Dynamic Environments Using Conformal Prediction. - Lars Lindemann; Matthew Cleaveland; Gihyun Shim; George J. Pappas (IEEE Robotics Autom. Lett., 2023)

Conformal Prediction Regions for Time Series Using Linear Complementarity Programming. - Matthew Cleaveland; Insup Lee 001; George J. Pappas; Lars Lindemann (AAAI, 2024)

Repairing Learning-Enabled Controllers While Preserving What Works. - Pengyuan Lu; Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001; Ivan Ruchkin (ICCPS, 2024)

Multi-modal conformal prediction regions by optimizing convex shape templates. - Renukanandan Tumu; Matthew Cleaveland; Rahul Mangharam; George J. Pappas; Lars Lindemann (L4DC, 2024)

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 001 (HSCC, 2025)

Conservative Perception Models for Probabilistic Model Checking. - Matthew Cleaveland; Pengyuan Lu; Oleg Sokolsky; Insup Lee 001; Ivan Ruchkin (CoRR, 2025)