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CTBENCH: A Library and Benchmark for Certified Training

CTBENCH: A Library and Benchmark for Certified Training

7 June 2024
Yuhao Mao
Stefan Balauca
Martin Vechev
    OOD
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Papers citing "CTBENCH: A Library and Benchmark for Certified Training"

39 / 39 papers shown
Title
On the Security Risks of ML-based Malware Detection Systems: A Survey
On the Security Risks of ML-based Malware Detection Systems: A Survey
Ping He
Yuhao Mao
Changjiang Li
Lorenzo Cavallaro
Ting Wang
Shouling Ji
53
0
0
16 May 2025
Average Certified Radius is a Poor Metric for Randomized Smoothing
Average Certified Radius is a Poor Metric for Randomized Smoothing
Chenhao Sun
Yuhao Mao
Mark Niklas Muller
Martin Vechev
AAML
63
0
0
09 Oct 2024
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
67
1
0
02 Oct 2024
Training Safe Neural Networks with Global SDP Bounds
Training Safe Neural Networks with Global SDP Bounds
Roman Soletskyi
David "davidad" Dalrymple
AAML
47
1
0
15 Sep 2024
Expressivity of ReLU-Networks under Convex Relaxations
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader
Mark Niklas Muller
Yuhao Mao
Martin Vechev
52
3
0
07 Nov 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang
Michael Backes
Xiao Zhang
AAML
86
1
0
06 Oct 2023
Understanding Certified Training with Interval Bound Propagation
Understanding Certified Training with Interval Bound Propagation
Yuhao Mao
Mark Niklas Muller
Marc Fischer
Martin Vechev
AAML
68
17
0
17 Jun 2023
Expressive Losses for Verified Robustness via Convex Combinations
Expressive Losses for Verified Robustness via Convex Combinations
Alessandro De Palma
Rudy Bunel
Krishnamurthy Dvijotham
M. P. Kumar
Robert Stanforth
A. Lomuscio
AAML
72
13
0
23 May 2023
Efficient Symbolic Reasoning for Neural-Network Verification
Efficient Symbolic Reasoning for Neural-Network Verification
Zi Wang
S. Jha
Krishnamurthy Dvijotham
Dvijotham
AAML
NAI
62
2
0
23 Mar 2023
Certified Training: Small Boxes are All You Need
Certified Training: Small Boxes are All You Need
Mark Niklas Muller
Franziska Eckert
Marc Fischer
Martin Vechev
AAML
53
47
0
10 Oct 2022
General Cutting Planes for Bound-Propagation-Based Neural Network
  Verification
General Cutting Planes for Bound-Propagation-Based Neural Network Verification
Huan Zhang
Shiqi Wang
Kaidi Xu
Linyi Li
Yue Liu
Suman Jana
Cho-Jui Hsieh
J. Zico Kolter
56
102
0
11 Aug 2022
IBP Regularization for Verified Adversarial Robustness via
  Branch-and-Bound
IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound
Alessandro De Palma
Rudy Bunel
Krishnamurthy Dvijotham
M. P. Kumar
Robert Stanforth
AAML
52
17
0
29 Jun 2022
Complete Verification via Multi-Neuron Relaxation Guided
  Branch-and-Bound
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
Claudio Ferrari
Mark Niklas Muller
Nikola Jovanović
Martin Vechev
67
86
0
30 Apr 2022
Certified Patch Robustness via Smoothed Vision Transformers
Certified Patch Robustness via Smoothed Vision Transformers
Hadi Salman
Saachi Jain
Eric Wong
Aleksander Mkadry
AAML
83
59
0
11 Oct 2021
Rethinking "Batch" in BatchNorm
Rethinking "Batch" in BatchNorm
Yuxin Wu
Justin Johnson
BDL
91
66
0
17 May 2021
Fast Certified Robust Training with Short Warmup
Fast Certified Robust Training with Short Warmup
Zhouxing Shi
Yihan Wang
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
AAML
49
56
0
31 Mar 2021
On the Paradox of Certified Training
On the Paradox of Certified Training
Nikola Jovanović
Mislav Balunović
Maximilian Baader
Martin Vechev
OOD
40
13
0
12 Feb 2021
Fast and Complete: Enabling Complete Neural Network Verification with
  Rapid and Massively Parallel Incomplete Verifiers
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu
Huan Zhang
Shiqi Wang
Yihan Wang
Suman Jana
Xue Lin
Cho-Jui Hsieh
68
183
0
27 Nov 2020
SoK: Certified Robustness for Deep Neural Networks
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Yue Liu
AAML
83
130
0
09 Sep 2020
Reliable evaluation of adversarial robustness with an ensemble of
  diverse parameter-free attacks
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
211
1,837
0
03 Mar 2020
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
257
833
0
19 Feb 2020
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
Yue Liu
Duane S. Boning
Cho-Jui Hsieh
AAML
67
346
0
14 Jun 2019
MNIST-C: A Robustness Benchmark for Computer Vision
MNIST-C: A Robustness Benchmark for Computer Vision
Norman Mu
Justin Gilmer
52
210
0
05 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OOD
VLM
165
3,429
0
28 Mar 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
130
2,036
0
08 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Nic Ford
Justin Gilmer
Nicholas Carlini
E. D. Cubuk
AAML
83
319
0
29 Jan 2019
Efficient Neural Network Robustness Certification with General
  Activation Functions
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang
Tsui-Wei Weng
Pin-Yu Chen
Cho-Jui Hsieh
Luca Daniel
AAML
87
760
0
02 Nov 2018
On the Effectiveness of Interval Bound Propagation for Training
  Verifiably Robust Models
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models
Sven Gowal
Krishnamurthy Dvijotham
Robert Stanforth
Rudy Bunel
Chongli Qin
J. Uesato
Relja Arandjelović
Timothy A. Mann
Pushmeet Kohli
AAML
73
556
0
30 Oct 2018
Scaling provable adversarial defenses
Scaling provable adversarial defenses
Eric Wong
Frank R. Schmidt
J. H. Metzen
J. Zico Kolter
AAML
73
446
0
31 May 2018
Averaging Weights Leads to Wider Optima and Better Generalization
Averaging Weights Leads to Wider Optima and Better Generalization
Pavel Izmailov
Dmitrii Podoprikhin
T. Garipov
Dmitry Vetrov
A. Wilson
FedML
MoMe
112
1,658
0
14 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
201
3,184
0
01 Feb 2018
Provable defenses against adversarial examples via the convex outer
  adversarial polytope
Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong
J. Zico Kolter
AAML
108
1,501
0
02 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
283
12,060
0
19 Jun 2017
How hard can it be? Estimating the difficulty of visual search in an
  image
How hard can it be? Estimating the difficulty of visual search in an image
Radu Tudor Ionescu
B. Alexe
Marius Leordeanu
Marius Popescu
Dim P. Papadopoulos
V. Ferrari
56
141
0
23 May 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
301
1,865
0
03 Feb 2017
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
439
43,277
0
11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
298
18,587
0
06 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
250
19,017
0
20 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
253
14,912
1
21 Dec 2013
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