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A Dual Approach to Scalable Verification of Deep Networks

A Dual Approach to Scalable Verification of Deep Networks

17 March 2018
Krishnamurthy Dvijotham
Dvijotham
Robert Stanforth
Sven Gowal
Timothy A. Mann
Pushmeet Kohli
ArXivPDFHTML

Papers citing "A Dual Approach to Scalable Verification of Deep Networks"

50 / 94 papers shown
Title
BURNS: Backward Underapproximate Reachability for Neural-Feedback-Loop Systems
BURNS: Backward Underapproximate Reachability for Neural-Feedback-Loop Systems
Chelsea Sidrane
Jana Tumova
32
0
0
06 May 2025
On Using Certified Training towards Empirical Robustness
On Using Certified Training towards Empirical Robustness
Alessandro De Palma
Serge Durand
Zakaria Chihani
François Terrier
Caterina Urban
OOD
AAML
38
1
0
02 Oct 2024
Neural Network Verification with Branch-and-Bound for General Nonlinearities
Neural Network Verification with Branch-and-Bound for General Nonlinearities
Zhouxing Shi
Qirui Jin
Zico Kolter
Suman Jana
Cho-Jui Hsieh
Huan Zhang
48
11
0
31 May 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar
Swagatam Haldar
Dennis L. Wei
Karthikeyan N. Ramamurthy
FAtt
40
2
0
17 Feb 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Devansh Bhardwaj
Kshitiz Kaushik
Sarthak Gupta
AAML
37
0
0
12 Feb 2024
Compositional Inductive Invariant Based Verification of Neural Network
  Controlled Systems
Compositional Inductive Invariant Based Verification of Neural Network Controlled Systems
Yuhao Zhou
S. Tripakis
29
1
0
17 Dec 2023
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
27
6
0
20 Jul 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks &
  Defenses
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses
Joana Cabral Costa
Tiago Roxo
Hugo Manuel Proença
Pedro R. M. Inácio
AAML
52
50
0
18 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
94
32
0
29 Apr 2023
Reachability Analysis of Neural Networks with Uncertain Parameters
Reachability Analysis of Neural Networks with Uncertain Parameters
Pierre-Jean Meyer
18
0
0
14 Mar 2023
Vertex-based reachability analysis for verifying ReLU deep neural
  networks
Vertex-based reachability analysis for verifying ReLU deep neural networks
João G. Zago
E. Camponogara
Eric A. Antonelo
AAML
29
2
0
27 Jan 2023
PCV: A Point Cloud-Based Network Verifier
PCV: A Point Cloud-Based Network Verifier
A. Sarker
Farzana Yasmin Ahmad
Matthew B. Dwyer
AAML
3DPC
33
1
0
27 Jan 2023
Improved techniques for deterministic l2 robustness
Improved techniques for deterministic l2 robustness
Sahil Singla
S. Feizi
AAML
23
9
0
15 Nov 2022
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
Ronghui Mu
Wenjie Ruan
Leandro Soriano Marcolino
Q. Ni
3DPC
32
10
0
15 Jul 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
29
43
0
24 Jun 2022
Can pruning improve certified robustness of neural networks?
Can pruning improve certified robustness of neural networks?
Zhangheng Li
Tianlong Chen
Linyi Li
Bo-wen Li
Zhangyang Wang
AAML
13
11
0
15 Jun 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms
  for Neural Networks
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks
Kiarash Mohammadi
Aishwarya Sivaraman
G. Farnadi
25
5
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
26
20
0
20 May 2022
Verifying Neural Networks Against Backdoor Attacks
Verifying Neural Networks Against Backdoor Attacks
Long H. Pham
Jun Sun
AAML
26
5
0
14 May 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization
  Perspective
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
26
33
0
27 Mar 2022
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Haoze Wu
Aleksandar Zeljić
Guy Katz
Clark W. Barrett
AAML
47
30
0
19 Mar 2022
A Unified View of SDP-based Neural Network Verification through
  Completely Positive Programming
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming
Robin Brown
Edward Schmerling
Navid Azizan
Marco Pavone
AAML
24
14
0
06 Mar 2022
On the Minimal Adversarial Perturbation for Deep Neural Networks with
  Provable Estimation Error
On the Minimal Adversarial Perturbation for Deep Neural Networks with Provable Estimation Error
Fabio Brau
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
29
7
0
04 Jan 2022
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model
  Checking
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking
Xidan Song
Edoardo Manino
Luiz Sena
E. Alves
Eddie Batista de Lima Filho
I. Bessa
M. Luján
Lucas C. Cordeiro
37
5
0
25 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
24
11
0
17 Nov 2021
Reachability analysis of neural networks using mixed monotonicity
Reachability analysis of neural networks using mixed monotonicity
Pierre-Jean Meyer
54
8
0
15 Nov 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of
  Neural Networks
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks
Mikhail Aleksandrovich Pautov
Nurislam Tursynbek
Marina Munkhoeva
Nikita Muravev
Aleksandr Petiushko
Ivan Oseledets
AAML
52
16
0
22 Sep 2021
The Second International Verification of Neural Networks Competition
  (VNN-COMP 2021): Summary and Results
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results
Stanley Bak
Changliu Liu
Taylor T. Johnson
NAI
25
112
0
31 Aug 2021
Neural Network Branch-and-Bound for Neural Network Verification
Neural Network Branch-and-Bound for Neural Network Verification
Florian Jaeckle
Jingyue Lu
M. P. Kumar
18
8
0
27 Jul 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator
  Splitting
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting
Shaoru Chen
Eric Wong
Zico Kolter
Mahyar Fazlyab
47
15
0
16 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
39
55
0
06 Apr 2021
Adversarial Robustness with Non-uniform Perturbations
Adversarial Robustness with Non-uniform Perturbations
Ece Naz Erdemir
Jeffrey Bickford
Luca Melis
Sergul Aydore
AAML
24
26
0
24 Feb 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
Fast Training of Provably Robust Neural Networks by SingleProp
Fast Training of Provably Robust Neural Networks by SingleProp
Akhilan Boopathy
Tsui-Wei Weng
Sijia Liu
Pin-Yu Chen
Gaoyuan Zhang
Luca Daniel
AAML
11
7
0
01 Feb 2021
DSRNA: Differentiable Search of Robust Neural Architectures
DSRNA: Differentiable Search of Robust Neural Architectures
Ramtin Hosseini
Xingyi Yang
P. Xie
OOD
AAML
29
50
0
11 Dec 2020
An efficient nonconvex reformulation of stagewise convex optimization
  problems
An efficient nonconvex reformulation of stagewise convex optimization problems
Rudy Bunel
Oliver Hinder
Srinadh Bhojanapalli
Krishnamurthy Dvijotham
Dvijotham
OffRL
35
14
0
27 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust
  Defense
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense
Maungmaung Aprilpyone
Hitoshi Kiya
29
57
0
02 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
SoK: Certified Robustness for Deep Neural Networks
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Bo-wen Li
AAML
33
128
0
09 Sep 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives
Adversarial Training and Provable Robustness: A Tale of Two Objectives
Jiameng Fan
Wenchao Li
AAML
23
20
0
13 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey
Adversarial Examples on Object Recognition: A Comprehensive Survey
A. Serban
E. Poll
Joost Visser
AAML
27
73
0
07 Aug 2020
Scaling Polyhedral Neural Network Verification on GPUs
Scaling Polyhedral Neural Network Verification on GPUs
Christoph Müller
F. Serre
Gagandeep Singh
Markus Püschel
Martin Vechev
AAML
29
56
0
20 Jul 2020
Abstraction based Output Range Analysis for Neural Networks
Abstraction based Output Range Analysis for Neural Networks
P. Prabhakar
Zahra Rahimi Afzal
33
62
0
18 Jul 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron
  Relaxations for Neural Network Verification
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
Christian Tjandraatmadja
Ross Anderson
Joey Huchette
Will Ma
Krunal Patel
J. Vielma
AAML
27
89
0
24 Jun 2020
DeepAbstract: Neural Network Abstraction for Accelerating Verification
DeepAbstract: Neural Network Abstraction for Accelerating Verification
P. Ashok
Vahid Hashemi
Jan Křetínský
S. Mohr
19
49
0
24 Jun 2020
Verifying Individual Fairness in Machine Learning Models
Verifying Individual Fairness in Machine Learning Models
Philips George John
Deepak Vijaykeerthy
Diptikalyan Saha
FaML
27
57
0
21 Jun 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and
  Faster Adversarial Robustness Proofs
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs
Christopher Brix
T. Noll
AAML
25
10
0
16 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES)
AI Research Considerations for Human Existential Safety (ARCHES)
Andrew Critch
David M. Krueger
30
50
0
30 May 2020
Encryption Inspired Adversarial Defense for Visual Classification
Encryption Inspired Adversarial Defense for Visual Classification
Maungmaung Aprilpyone
Hitoshi Kiya
18
32
0
16 May 2020
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