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A Statistical Approach to Assessing Neural Network Robustness

A Statistical Approach to Assessing Neural Network Robustness

17 November 2018
Stefan Webb
Tom Rainforth
Yee Whye Teh
M. P. Kumar
    AAML
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Papers citing "A Statistical Approach to Assessing Neural Network Robustness"

20 / 20 papers shown
Title
Estimating the Probabilities of Rare Outputs in Language Models
Estimating the Probabilities of Rare Outputs in Language Models
Gabriel Wu
Jacob Hilton
AAML
UQCV
60
2
0
17 Oct 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
35
3
0
12 Apr 2024
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled
  Safety Critical Systems
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems
Saddek Bensalem
Chih-Hong Cheng
Wei Huang
Xiaowei Huang
Changshun Wu
Xingyu Zhao
AAML
32
6
0
20 Jul 2023
Provable Preimage Under-Approximation for Neural Networks (Full Version)
Provable Preimage Under-Approximation for Neural Networks (Full Version)
Xiyue Zhang
Benjie Wang
Marta Z. Kwiatkowska
AAML
36
7
0
05 May 2023
Selecting Models based on the Risk of Damage Caused by Adversarial
  Attacks
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
Jona Klemenc
Holger Trittenbach
AAML
32
1
0
28 Jan 2023
QEBVerif: Quantization Error Bound Verification of Neural Networks
QEBVerif: Quantization Error Bound Verification of Neural Networks
Yedi Zhang
Fu Song
Jun Sun
MQ
26
11
0
06 Dec 2022
PRoA: A Probabilistic Robustness Assessment against Functional
  Perturbations
PRoA: A Probabilistic Robustness Assessment against Functional Perturbations
Tianle Zhang
Wenjie Ruan
J. Fieldsend
AAML
18
21
0
05 Jul 2022
Hierarchical Distribution-Aware Testing of Deep Learning
Hierarchical Distribution-Aware Testing of Deep Learning
Wei Huang
Xingyu Zhao
Alec Banks
V. Cox
Xiaowei Huang
OOD
AAML
47
10
0
17 May 2022
Adversarial Training for High-Stakes Reliability
Adversarial Training for High-Stakes Reliability
Daniel M. Ziegler
Seraphina Nix
Lawrence Chan
Tim Bauman
Peter Schmidt-Nielsen
...
Noa Nabeshima
Benjamin Weinstein-Raun
D. Haas
Buck Shlegeris
Nate Thomas
AAML
38
59
0
03 May 2022
A Simple and Efficient Sampling-based Algorithm for General Reachability
  Analysis
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis
T. Lew
Lucas Janson
Riccardo Bonalli
Marco Pavone
32
18
0
10 Dec 2021
ε-weakened Robustness of Deep Neural Networks
ε-weakened Robustness of Deep Neural Networks
Pei Huang
Yuting Yang
Minghao Liu
Fuqi Jia
Feifei Ma
Jian Zhang
AAML
27
18
0
29 Oct 2021
RoMA: a Method for Neural Network Robustness Measurement and Assessment
RoMA: a Method for Neural Network Robustness Measurement and Assessment
Natan Levy
Guy Katz
OOD
AAML
12
13
0
21 Oct 2021
Assessing the Reliability of Deep Learning Classifiers Through
  Robustness Evaluation and Operational Profiles
Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles
Xingyu Zhao
Wei Huang
Alec Banks
V. Cox
David Flynn
S. Schewe
Xiaowei Huang
AAML
UQCV
41
21
0
02 Jun 2021
Data-Driven Certification of Neural Networks with Random Input Noise
Data-Driven Certification of Neural Networks with Random Input Noise
Brendon G. Anderson
Somayeh Sojoudi
AAML
17
11
0
02 Oct 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
Aman Sinha
Matthew O'Kelly
Russ Tedrake
John C. Duchi
41
48
0
24 Aug 2020
Quantitative Verification of Neural Networks And its Security
  Applications
Quantitative Verification of Neural Networks And its Security Applications
Teodora Baluta
Shiqi Shen
Shweta Shinde
Kuldeep S. Meel
P. Saxena
AAML
24
104
0
25 Jun 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks
Statistical Guarantees for the Robustness of Bayesian Neural Networks
L. Cardelli
Marta Kwiatkowska
Luca Laurenti
Nicola Paoletti
A. Patané
Matthew Wicker
AAML
31
54
0
05 Mar 2019
Output Reachable Set Estimation and Verification for Multi-Layer Neural
  Networks
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks
Weiming Xiang
Hoang-Dung Tran
Taylor T. Johnson
88
293
0
09 Aug 2017
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
251
1,842
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
183
933
0
21 Oct 2016
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