Formal verification of unknown stochastic systems via non-parametric estimation
Z Zhang, C Ma, S Soudijani… - … Conference on Artificial …, 2024 - proceedings.mlr.press
A novel data-driven method for formal verification is proposed to study complex systems
operating in safety-critical domains. The proposed approach is able to formally verify …
operating in safety-critical domains. The proposed approach is able to formally verify …
Multi-modal conformal prediction regions by optimizing convex shape templates
Conformal prediction is a statistical tool for producing prediction regions for machine
learning models that are valid with high probability. A key component of conformal prediction …
learning models that are valid with high probability. A key component of conformal prediction …
Single Trajectory Conformal Prediction
B Lee, N Matni - arXiv preprint arXiv:2406.01570, 2024 - arxiv.org
We study the performance of risk-controlling prediction sets (RCPS), an empirical risk
minimization-based formulation of conformal prediction, with a single trajectory of temporally …
minimization-based formulation of conformal prediction, with a single trajectory of temporally …
Statistical reachability analysis of stochastic cyber-physical systems under distribution shift
Reachability analysis is a popular method to give safety guarantees for stochastic cyber-
physical systems (SCPSs) that takes in a symbolic description of the system dynamics and …
physical systems (SCPSs) that takes in a symbolic description of the system dynamics and …
Formal Verification and Control with Conformal Prediction
In this survey, we design formal verification and control algorithms for autonomous systems
with practical safety guarantees using conformal prediction (CP), a statistical tool for …
with practical safety guarantees using conformal prediction (CP), a statistical tool for …
Scenario Approach and Conformal Prediction for Verification of Unknown Systems via Data-Driven Abstractions
Verification of uncertain, complex dynamical systems is crucial in the modern day world. An
increasingly common method to verify complex logic specifications for dynamical systems …
increasingly common method to verify complex logic specifications for dynamical systems …
Probabilistic Reachability of Discrete-Time Nonlinear Stochastic Systems
Z Liu, S Jafarpour, Y Chen - arXiv preprint arXiv:2409.09334, 2024 - arxiv.org
In this paper we study the reachability problem for discrete-time nonlinear stochastic
systems. Our goal is to present a unified framework for calculating the probabilistic …
systems. Our goal is to present a unified framework for calculating the probabilistic …
Forward Reachability for Discrete-Time Nonlinear Stochastic Systems via Mixed-Monotonicity and Stochastic Order
V Sivaramakrishnan, RA Devonport, M Arcak… - arXiv preprint arXiv …, 2024 - arxiv.org
We present a method to overapproximate forward stochastic reach sets of discrete-time,
stochastic nonlinear systems with interval geometry. This is made possible by extending the …
stochastic nonlinear systems with interval geometry. This is made possible by extending the …
3.3 Neuro-symbolic Model Learning for Controller Synthesis and Verification
J Deshmukh - Model Learning for Improved Trustworthiness in … - drops.dagstuhl.de
Synthesizing control policies for high-dimensional, highly nonlinear/hybrid systems that
guarantee satisfaction of safety and performance properties of the system is a significant …
guarantee satisfaction of safety and performance properties of the system is a significant …