7 papers · 1 filter
Conformal Prediction Regions for Continuous-Time Trajectories under Random Sampling
Joaquin Alvarez, Matteo Sesia, Jyotirmoy V. Deshmukh +1
Uncertainty quantification for continuous-time trajectories is a prerequisite in many safety-critical engineering domains. However, a major challenge in data-driven uncertainty qua…
When Environments Shift: Safe Planning with Generative Priors and Robust Conformal Prediction
Kaizer Rahaman, Jyotirmoy V. Deshmukh, Ashish R. Hota +1
Autonomous systems operate in environments that may change over time. An example is the control of a self-driving vehicle among pedestrians and human-controlled vehicles whose beha…
Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints
Junyang Cai, Weimin Huang, Brendan Long +4
Motion-planning problems with temporal-logic or chance constraints are often encoded as mixed-integer linear programs (MILPs). Although these encodings provide rigorous specificati…
Distributionally Robust Predictive Runtime Verification under Spatio-Temporal Logic Specifications
Yiqi Zhao, Emily Zhu, Bardh Hoxha +3
Cyber-physical systems (CPS) designed in simulators, often consisting of multiple interacting agents (e.g. in multi-agent formations), behave differently in the real-world. We want…
Conformal Predictive Programming for Chance Constrained Optimization
Yiqi Zhao, Xinyi Yu, Matteo Sesia +2
We propose conformal predictive programming (CPP), a framework to solve chance constrained optimization problems, i.e., optimization problems with constraints that are functions of…
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift
Yiqi Zhao, Bardh Hoxha, Georgios Fainekos +2
Cyber-physical systems (CPS) designed in simulators behave differently in the real-world. Once they are deployed in the real-world, we would hence like to predict system failures d…
Data-Driven Reachability Analysis of Stochastic Dynamical Systems with Conformal Inference
Navid Hashemi, Xin Qin, Lars Lindemann +1
We consider data-driven reachability analysis of discrete-time stochastic dynamical systems using conformal inference. We assume that we are not provided with a symbolic representa…