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Verification of deep probabilistic models

Verification of deep probabilistic models

6 December 2018
Krishnamurthy Dvijotham
M. Garnelo
Alhussein Fawzi
Pushmeet Kohli
ArXivPDFHTML

Papers citing "Verification of deep probabilistic models"

16 / 16 papers shown
Title
Probabilistic Verification of ReLU Neural Networks via Characteristic
  Functions
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions
Joshua Pilipovsky
Vignesh Sivaramakrishnan
Meeko Oishi
Panagiotis Tsiotras
37
5
0
03 Dec 2022
The Neural Process Family: Survey, Applications and Perspectives
The Neural Process Family: Survey, Applications and Perspectives
Saurav Jha
Dong Gong
Xuesong Wang
Richard Turner
L. Yao
BDL
83
24
0
01 Sep 2022
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
Make Sure You're Unsure: A Framework for Verifying Probabilistic
  Specifications
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
Leonard Berrada
Sumanth Dathathri
Krishnamurthy Dvijotham
Robert Stanforth
Rudy Bunel
J. Uesato
Sven Gowal
M. P. Kumar
AAML
OOD
30
17
0
18 Feb 2021
The Vulnerability of Semantic Segmentation Networks to Adversarial
  Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing
Andreas Bär
Jonas Löhdefink
Nikhil Kapoor
Serin Varghese
Fabian Hüger
Peter Schlicht
Tim Fingscheidt
AAML
113
33
0
11 Jan 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
SoK: Certified Robustness for Deep Neural Networks
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Bo-wen Li
AAML
38
128
0
09 Sep 2020
Robustness Certification of Generative Models
Robustness Certification of Generative Models
M. Mirman
Timon Gehr
Martin Vechev
AAML
43
22
0
30 Apr 2020
Probabilistic Safety for Bayesian Neural Networks
Probabilistic Safety for Bayesian Neural Networks
Matthew Wicker
Luca Laurenti
A. Patané
Marta Z. Kwiatkowska
AAML
14
52
0
21 Apr 2020
Enhancing Certifiable Robustness via a Deep Model Ensemble
Enhancing Certifiable Robustness via a Deep Model Ensemble
Huan Zhang
Minhao Cheng
Cho-Jui Hsieh
33
9
0
31 Oct 2019
Probabilistic Verification and Reachability Analysis of Neural Networks
  via Semidefinite Programming
Probabilistic Verification and Reachability Analysis of Neural Networks via Semidefinite Programming
Mahyar Fazlyab
M. Morari
George J. Pappas
AAML
40
41
0
09 Oct 2019
Towards Stable and Efficient Training of Verifiably Robust Neural
  Networks
Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Huan Zhang
Hongge Chen
Chaowei Xiao
Sven Gowal
Robert Stanforth
Bo-wen Li
Duane S. Boning
Cho-Jui Hsieh
AAML
17
344
0
14 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
A Convex Relaxation Barrier to Tight Robustness Verification of Neural
  Networks
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Hadi Salman
Greg Yang
Huan Zhang
Cho-Jui Hsieh
Pengchuan Zhang
AAML
52
263
0
23 Feb 2019
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic
  Approach
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach
Tsui-Wei Weng
Pin-Yu Chen
Lam M. Nguyen
M. Squillante
Ivan Oseledets
Luca Daniel
AAML
21
30
0
18 Dec 2018
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
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