Verifying Controllers with Convolutional Neural Network-based
Perception: A Case for Intelligible, Safe, and Precise Abstractions

Verifying Controllers with Convolutional Neural Network-based Perception: A Case for Intelligible, Safe, and Precise Abstractions

10 November 2021

Sasa Misailovic

Sayan Mitra

Papers citing "Verifying Controllers with Convolutional Neural Network-based Perception: A Case for Intelligible, Safe, and Precise Abstractions"

6 / 6 papers shown

Title
Scenario-based Compositional Verification of Autonomous Systems with Neural Perception Christopher Watson Rajeev Alur Divya Gopinath Ravi Mangal C. Păsăreanu 53 0 0 29 Apr 2025
Formal Verification and Control with Conformal Prediction Lars Lindemann Yiqi Zhao Xinyi Yu George J. Pappas Jyotirmoy V. Deshmukh 60 14 0 31 Aug 2024
Perceive With Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception Anushri Dixit Zhiting Mei Meghan Booker Mariko Storey-Matsutani Mariko Storey-Matsutani Allen Z. Ren Ola Shorinwa Anirudha Majumdar 29 5 0 13 Mar 2024
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study C. Păsăreanu Ravi Mangal D. Gopinath Sinem Getir Yaman Calum Imrie R. Calinescu Huafeng Yu 27 29 0 06 Feb 2023
Assuring Safety of Vision-Based Swarm Formation Control Chiao Hsieh Yubin Koh Yangge Li Sayan Mitra 15 4 0 03 Oct 2022
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 226 1,835 0 03 Feb 2017