Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems

24 August 2020

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

38 / 38 papers shown

Title
Density Ratio Estimation with Conditional Probability Paths Hanlin Yu Arto Klami Aapo Hyvarinen Anna Korba Omar Chehab 81 0 0 04 Feb 2025
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net Wenjie Luo Binh Yang R. Urtasun 3DPC 44 620 0 22 Dec 2020
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems Anthony Corso Robert J. Moss Mark Koren Ritchie Lee Mykel J. Kochenderfer 51 175 0 06 May 2020
Neuroevolution of Self-Interpretable Agents Yujin Tang Duong Nguyen David R Ha 53 111 0 18 Mar 2020
Trustworthy AI Jeannette M. Wing 35 218 0 14 Feb 2020
Anomaly Detection with Density Estimation Benjamin Nachman David Shih 18 218 0 14 Jan 2020
Efficient Black-box Assessment of Autonomous Vehicle Safety J. Norden Matthew O'Kelly Aman Sinha 43 66 0 08 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 110 1,662 0 05 Dec 2019
Case Study: Verifying the Safety of an Autonomous Racing Car with a Neural Network Controller Radoslav Ivanov Taylor J. Carpenter James Weimer Rajeev Alur George J. Pappas Insup Lee 37 81 0 24 Oct 2019
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients Yuansi Chen Raaz Dwivedi Martin J. Wainwright Bin Yu 25 101 0 29 May 2019
Monocular Plan View Networks for Autonomous Driving Dequan Wang Coline Devin Qi-Zhi Cai Philipp Krahenbuhl Trevor Darrell 38 81 0 16 May 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 40 105 0 09 Mar 2019
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst Mayank Bansal A. Krizhevsky A. Ogale OOD 49 736 0 07 Dec 2018
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures Junhui Yin Jiayan Qiu Csaba Szepesvári Siqing Zhang Avraham Ruderman Jiyang Xie Krishnamurthy Dvijotham Zhanyu Ma N. Heess Pushmeet Kohli AAML 49 80 0 04 Dec 2018
In-silico Risk Analysis of Personalized Artificial Pancreas Controllers via Rare-event Simulation Matthew O'Kelly Aman Sinha J. Norden Hongseok Namkoong 14 1 0 02 Dec 2018
A Statistical Approach to Assessing Neural Network Robustness Stefan Webb Tom Rainforth Yee Whye Teh M. P. Kumar AAML 45 82 0 17 Nov 2018
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation Matthew O'Kelly Aman Sinha Hongseok Namkoong John C. Duchi Russ Tedrake 39 217 0 31 Oct 2018
World Models David R Ha Jürgen Schmidhuber SyDa 88 1,050 0 27 Mar 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 51 1,862 0 02 Jan 2018
Evaluating Robustness of Neural Networks with Mixed Integer Programming Vincent Tjeng Kai Y. Xiao Russ Tedrake AAML 63 117 0 20 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 71 858 0 29 Oct 2017
Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions Oren Mangoubi Aaron Smith 94 106 0 23 Aug 2017
On a Formal Model of Safe and Scalable Self-driving Cars Shai Shalev-Shwartz Shaked Shammah Amnon Shashua 22 736 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 188 11,962 0 19 Jun 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 96 1,340 0 19 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 282 1,849 0 03 Feb 2017
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 74 1,805 0 15 Jun 2016
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 162 5,048 0 05 Jun 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 200 17,235 0 17 Feb 2016
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm Alain Durmus Eric Moulines 45 410 0 17 Jul 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 223 4,143 0 21 May 2015
Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations Peyman Mohajerin Esfahani Daniel Kuhn 41 1,641 0 19 May 2015
Optimal rates for zero-order convex optimization: the power of two function evaluations John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono 43 480 0 07 Dec 2013
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions Ari Pakman Liam Paninski 74 80 0 09 Nov 2013
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions Shiwei Lan Bo Zhou Babak Shahbaba 59 58 0 17 Sep 2013
Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians Ari Pakman Liam Paninski 58 221 0 20 Aug 2012
MCMC using Hamiltonian dynamics Radford M. Neal 280 3,278 0 09 Jun 2012
Split Hamiltonian Monte Carlo Babak Shahbaba Shiwei Lan W. Johnson Radford M. Neal 124 92 0 29 Jun 2011