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Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems

Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems

24 August 2020
Aman Sinha
Matthew O'Kelly
Russ Tedrake
John C. Duchi
ArXivPDFHTML

Papers citing "Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems"

10 / 10 papers shown
Title
Density Ratio Estimation with Conditional Probability Paths
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu
Arto Klami
Aapo Hyvarinen
Anna Korba
Omar Chehab
53
0
0
04 Feb 2025
Diffusion-Based Failure Sampling for Cyber-Physical Systems
Diffusion-Based Failure Sampling for Cyber-Physical Systems
Harrison Delecki
Marc R. Schlichting
Mansur Arief
Anthony Corso
Marcell Vazquez-Chanlatte
Mykel J. Kochenderfer
DiffM
18
0
0
20 Jun 2024
A Direct Importance Sampling-based Framework for Rare Event Uncertainty
  Quantification in Non-Gaussian Spaces
A Direct Importance Sampling-based Framework for Rare Event Uncertainty Quantification in Non-Gaussian Spaces
Elsayed M. Eshra
Konstantinos G. Papakonstantinou
Hamed Nikbakht
14
0
0
23 May 2024
Adaptive Testing Environment Generation for Connected and Automated
  Vehicles with Dense Reinforcement Learning
Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning
Jingxuan Yang
Ruoxuan Bai
Haoyuan Ji
Yi Zhang
Jianming Hu
Shuo Feng
17
3
0
29 Feb 2024
End-to-End Supervised Multilabel Contrastive Learning
End-to-End Supervised Multilabel Contrastive Learning
A. Sajedi
Samir Khaki
Konstantinos N. Plataniotis
Mahdi S. Hosseini
SSL
6
8
0
08 Jul 2023
A Survey on Scenario-Based Testing for Automated Driving Systems in
  High-Fidelity Simulation
A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation
Ziyuan Zhong
Yun Tang
Yuan Zhou
V. Neves
Yang Liu
Baishakhi Ray
25
60
0
02 Dec 2021
Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey
Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey
M. Askarpour
Alan Wassyng
M. Lawford
R. Paige
Z. Diskin
12
0
0
29 Nov 2021
Probabilistic Metamodels for an Efficient Characterization of Complex
  Driving Scenarios
Probabilistic Metamodels for an Efficient Characterization of Complex Driving Scenarios
Max Winkelmann
Mike Kohlhoff
H. Tadjine
Steffen Müller
9
9
0
06 Oct 2021
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
219
1,818
0
03 Feb 2017
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
127
3,260
0
09 Jun 2012
1