ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2112.09625
  4. Cited By
Provable Adversarial Robustness in the Quantum Model

Provable Adversarial Robustness in the Quantum Model

17 December 2021
Khashayar Barooti
Grzegorz Gluch
R. Urbanke
    AAML
    OOD
ArXivPDFHTML

Papers citing "Provable Adversarial Robustness in the Quantum Model"

11 / 11 papers shown
Title
Out of Distribution Generalization in Machine Learning
Out of Distribution Generalization in Machine Learning
Martín Arjovsky
OOD
CML
45
93
0
03 Mar 2021
Adversarial Robustness: What fools you makes you stronger
Adversarial Robustness: What fools you makes you stronger
Grzegorz Gluch
R. Urbanke
AAML
97
2
0
10 Feb 2021
Adversarially Robust Learning with Unknown Perturbation Sets
Adversarially Robust Learning with Unknown Perturbation Sets
Omar Montasser
Steve Hanneke
Nathan Srebro
AAML
66
27
0
03 Feb 2021
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial
  Test Examples
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
S. Goldwasser
Adam Tauman Kalai
Y. Kalai
Omar Montasser
AAML
48
40
0
10 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image
  Classification
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori
Achal Dave
Vaishaal Shankar
Nicholas Carlini
Benjamin Recht
Ludwig Schmidt
OOD
117
546
0
01 Jul 2020
Adversarial Training and Robustness for Multiple Perturbations
Adversarial Training and Robustness for Multiple Perturbations
Florian Tramèr
Dan Boneh
AAML
SILM
75
378
0
30 Apr 2019
Do ImageNet Classifiers Generalize to ImageNet?
Do ImageNet Classifiers Generalize to ImageNet?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OOD
SSeg
VLM
113
1,715
0
13 Feb 2019
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
102
1,781
0
30 May 2018
Adversarial examples from computational constraints
Adversarial examples from computational constraints
Sébastien Bubeck
Eric Price
Ilya P. Razenshteyn
AAML
114
231
0
25 May 2018
Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
169
3,271
0
05 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
270
14,927
1
21 Dec 2013
1