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Measuring Neural Net Robustness with Constraints

Measuring Neural Net Robustness with Constraints

24 May 2016
Osbert Bastani
Yani Andrew Ioannou
Leonidas Lampropoulos
Dimitrios Vytiniotis
A. Nori
A. Criminisi
    AAML
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Papers citing "Measuring Neural Net Robustness with Constraints"

50 / 77 papers shown
Title
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels
Verification of Neural Networks against Convolutional Perturbations via Parameterised Kernels
Benedikt Brückner
Alessio Lomuscio
AAML
59
0
0
07 Nov 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in
  Deep Robust Classifiers
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
Jonas Ngnawé
Sabyasachi Sahoo
Y. Pequignot
Frédéric Precioso
Christian Gagné
AAML
47
0
0
26 Jun 2024
A Certified Proof Checker for Deep Neural Network Verification
A Certified Proof Checker for Deep Neural Network Verification
Remi Desmartin
Omri Isac
Ekaterina Komendantskaya
Kathrin Stark
Grant Passmore
Guy Katz
43
3
0
17 May 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
Verifiable Boosted Tree Ensembles
Verifiable Boosted Tree Ensembles
Stefano Calzavara
Lorenzo Cazzaro
Claudio Lucchese
Giulio Ermanno Pibiri
AAML
49
0
0
22 Feb 2024
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep
  Neural Networks
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
Yang Wang
B. Dong
Ke Xu
Haiyin Piao
Yufei Ding
Baocai Yin
Xin Yang
AAML
39
3
0
10 Oct 2023
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural
  Networks
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks
Natan Levy
Raz Yerushalmi
Guy Katz
AAML
30
1
0
05 Jan 2023
Efficiently Finding Adversarial Examples with DNN Preprocessing
Efficiently Finding Adversarial Examples with DNN Preprocessing
Avriti Chauhan
Mohammad Afzal
Hrishikesh Karmarkar
Y. Elboher
Kumar Madhukar
Guy Katz
AAML
37
0
0
16 Nov 2022
Adversarial Purification with the Manifold Hypothesis
Adversarial Purification with the Manifold Hypothesis
Zhaoyuan Yang
Zhiwei Xu
Jing Zhang
Richard I. Hartley
Peter Tu
AAML
24
5
0
26 Oct 2022
Sound and Complete Verification of Polynomial Networks
Sound and Complete Verification of Polynomial Networks
Elias Abad Rocamora
Mehmet Fatih Şahin
Fanghui Liu
Grigorios G. Chrysos
V. Cevher
28
5
0
15 Sep 2022
Understanding Adversarial Robustness of Vision Transformers via Cauchy
  Problem
Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem
Zheng Wang
Wenjie Ruan
ViT
44
8
0
01 Aug 2022
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal
  Verification Perspective
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Mark Huasong Meng
Guangdong Bai
Sin Gee Teo
Zhe Hou
Yan Xiao
Yun Lin
Jin Song Dong
AAML
37
43
0
24 Jun 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An
  Overview
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview
Florian Karl
Tobias Pielok
Julia Moosbauer
Florian Pfisterer
Stefan Coors
...
Jakob Richter
Michel Lang
Eduardo C. Garrido-Merchán
Juergen Branke
B. Bischl
AI4CE
31
57
0
15 Jun 2022
Neural Network Verification with Proof Production
Neural Network Verification with Proof Production
Omri Isac
Clark W. Barrett
Min Zhang
Guy Katz
AAML
40
20
0
01 Jun 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks
CertiFair: A Framework for Certified Global Fairness of Neural Networks
Haitham Khedr
Yasser Shoukry
FedML
31
20
0
20 May 2022
Software Testing for Machine Learning
Software Testing for Machine Learning
D. Marijan
A. Gotlieb
AAML
30
27
0
30 Apr 2022
If a Human Can See It, So Should Your System: Reliability Requirements
  for Machine Vision Components
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components
Boyue Caroline Hu
Lina Marsso
Krzysztof Czarnecki
Rick Salay
Huakun Shen
Marsha Chechik
24
21
0
08 Feb 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural
  Networks
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks
Matan Ostrovsky
Clark W. Barrett
Guy Katz
45
26
0
06 Jan 2022
Curriculum Learning for Safe Mapless Navigation
Curriculum Learning for Safe Mapless Navigation
Luca Marzari
Davide Corsi
Enrico Marchesini
Alessandro Farinelli
30
14
0
23 Dec 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks
The Fundamental Limits of Interval Arithmetic for Neural Networks
M. Mirman
Maximilian Baader
Martin Vechev
32
6
0
09 Dec 2021
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution
  Detection
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection
Nikolaos Dionelis
Mehrdad Yaghoobi
Sotirios A. Tsaftaris
OODD
19
4
0
30 Nov 2021
Fast BATLLNN: Fast Box Analysis of Two-Level Lattice Neural Networks
Fast BATLLNN: Fast Box Analysis of Two-Level Lattice Neural Networks
James Ferlez
Haitham Khedr
Yasser Shoukry
29
12
0
17 Nov 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
Lyapunov-stable neural-network control
Lyapunov-stable neural-network control
Hongkai Dai
Benoit Landry
Lujie Yang
Marco Pavone
Russ Tedrake
26
119
0
29 Sep 2021
Evaluating the Robustness of Trigger Set-Based Watermarks Embedded in
  Deep Neural Networks
Evaluating the Robustness of Trigger Set-Based Watermarks Embedded in Deep Neural Networks
Suyoung Lee
Wonho Song
Suman Jana
M. Cha
Sooel Son
AAML
27
13
0
18 Jun 2021
DNNV: A Framework for Deep Neural Network Verification
DNNV: A Framework for Deep Neural Network Verification
David Shriver
Sebastian G. Elbaum
Matthew B. Dwyer
21
31
0
26 May 2021
A Review of Formal Methods applied to Machine Learning
A Review of Formal Methods applied to Machine Learning
Caterina Urban
Antoine Miné
49
55
0
06 Apr 2021
Robust Machine Learning Systems: Challenges, Current Trends,
  Perspectives, and the Road Ahead
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead
Mohamed Bennai
Mahum Naseer
T. Theocharides
C. Kyrkou
O. Mutlu
Lois Orosa
Jungwook Choi
OOD
81
100
0
04 Jan 2021
Robust and Stable Black Box Explanations
Robust and Stable Black Box Explanations
Himabindu Lakkaraju
Nino Arsov
Osbert Bastani
AAML
FAtt
24
84
0
12 Nov 2020
An SMT-Based Approach for Verifying Binarized Neural Networks
An SMT-Based Approach for Verifying Binarized Neural Networks
Guy Amir
Haoze Wu
Clark W. Barrett
Guy Katz
27
58
0
05 Nov 2020
Transferable Universal Adversarial Perturbations Using Generative Models
Transferable Universal Adversarial Perturbations Using Generative Models
Atiyeh Hashemi
Andreas Bär
S. Mozaffari
Tim Fingscheidt
AAML
30
17
0
28 Oct 2020
Safety Verification of Model Based Reinforcement Learning Controllers
Safety Verification of Model Based Reinforcement Learning Controllers
Akshita Gupta
Inseok Hwang
37
5
0
21 Oct 2020
Evaluating the Safety of Deep Reinforcement Learning Models using
  Semi-Formal Verification
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification
Davide Corsi
Enrico Marchesini
Alessandro Farinelli
OffRL
14
2
0
19 Oct 2020
Characterizing and Taming Model Instability Across Edge Devices
Characterizing and Taming Model Instability Across Edge Devices
Eyal Cidon
Evgenya Pergament
Zain Asgar
Asaf Cidon
Sachin Katti
14
7
0
18 Oct 2020
Deep Learning & Software Engineering: State of Research and Future
  Directions
Deep Learning & Software Engineering: State of Research and Future Directions
P. Devanbu
Matthew B. Dwyer
Sebastian G. Elbaum
M. Lowry
Kevin Moran
Denys Poshyvanyk
Baishakhi Ray
Rishabh Singh
Xiangyu Zhang
11
22
0
17 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and
  Adversarial Examples
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Timo Freiesleben
GAN
46
62
0
11 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey
Adversarial Examples on Object Recognition: A Comprehensive Survey
A. Serban
E. Poll
Joost Visser
AAML
32
73
0
07 Aug 2020
Robustifying Reinforcement Learning Agents via Action Space Adversarial
  Training
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training
Kai Liang Tan
Yasaman Esfandiari
Xian Yeow Lee
Aakanksha
Soumik Sarkar
AAML
26
55
0
14 Jul 2020
Arms Race in Adversarial Malware Detection: A Survey
Arms Race in Adversarial Malware Detection: A Survey
Deqiang Li
Qianmu Li
Yanfang Ye
Shouhuai Xu
AAML
24
52
0
24 May 2020
ReluDiff: Differential Verification of Deep Neural Networks
ReluDiff: Differential Verification of Deep Neural Networks
Brandon Paulsen
Jingbo Wang
Chao Wang
30
53
0
10 Jan 2020
An Abstraction-Based Framework for Neural Network Verification
An Abstraction-Based Framework for Neural Network Verification
Y. Elboher
Justin Emile Gottschlich
Guy Katz
27
122
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
Testing and verification of neural-network-based safety-critical control
  software: A systematic literature review
Testing and verification of neural-network-based safety-critical control software: A systematic literature review
Jin Zhang
Jingyue Li
27
47
0
05 Oct 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary
  Attack
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce
Matthias Hein
AAML
43
475
0
03 Jul 2019
Machine Learning Testing: Survey, Landscapes and Horizons
Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang
Mark Harman
Lei Ma
Yang Liu
VLM
AILaw
39
741
0
19 Jun 2019
Testing DNN Image Classifiers for Confusion & Bias Errors
Testing DNN Image Classifiers for Confusion & Bias Errors
Yuchi Tian
Ziyuan Zhong
Vicente Ordonez
Gail E. Kaiser
Baishakhi Ray
24
52
0
20 May 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the
  Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer
  Domain
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain
Lei Bu
Yuchao Duan
Fu Song
Zhe Zhao
AAML
37
18
0
19 May 2019
How is Gaze Influenced by Image Transformations? Dataset and Model
How is Gaze Influenced by Image Transformations? Dataset and Model
Zhaohui Che
Ali Borji
Guangtao Zhai
Xiongkuo Min
G. Guo
P. Le Callet
27
76
0
16 May 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the
  Union of Polytopes
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes
Matt Jordan
Justin Lewis
A. Dimakis
AAML
35
57
0
20 Mar 2019
Algorithms for Verifying Deep Neural Networks
Algorithms for Verifying Deep Neural Networks
Changliu Liu
Tomer Arnon
Christopher Lazarus
Christopher A. Strong
Clark W. Barrett
Mykel J. Kochenderfer
AAML
41
394
0
15 Mar 2019
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