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Closing the Loop on Runtime Monitors with Fallback-Safe MPC

Closing the Loop on Runtime Monitors with Fallback-Safe MPC

15 September 2023
Rohan Sinha
Edward Schmerling
Marco Pavone
ArXivPDFHTML

Papers citing "Closing the Loop on Runtime Monitors with Fallback-Safe MPC"

9 / 9 papers shown
Title
Formal Verification and Control with Conformal Prediction
Formal Verification and Control with Conformal Prediction
Lars Lindemann
Yiqi Zhao
Xinyi Yu
George J. Pappas
Jyotirmoy V. Deshmukh
57
13
0
31 Aug 2024
Perceive With Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception
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
Conformal Decision Theory: Safe Autonomous Decisions from Imperfect
  Predictions
Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions
Jordan Lekeufack
Anastasios Nikolas Angelopoulos
Andrea V. Bajcsy
Michael I. Jordan
Jitendra Malik
OffRL
26
28
0
09 Oct 2023
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
171
870
0
21 Oct 2021
Sample-Efficient Safety Assurances using Conformal Prediction
Sample-Efficient Safety Assurances using Conformal Prediction
Rachel Luo
Shengjia Zhao
Jonathan Kuck
B. Ivanovic
Silvio Savarese
Edward Schmerling
Marco Pavone
48
56
0
28 Sep 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey
  of Emerging Trends
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends
Q. Rahman
Peter Corke
Feras Dayoub
OOD
27
51
0
05 Jan 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on
  Open Problems
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
329
1,944
0
04 May 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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