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Adversarial Purification for Data-Driven Power System Event Classifiers
  with Diffusion Models

Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models

13 November 2023
Yuanbin Cheng
Koji Yamashita
Jim Follum
Nanpeng Yu
    AAML
ArXivPDFHTML

Papers citing "Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models"

9 / 9 papers shown
Title
Diffusion Models for Adversarial Purification
Diffusion Models for Adversarial Purification
Weili Nie
Brandon Guo
Yujia Huang
Chaowei Xiao
Arash Vahdat
Anima Anandkumar
WIGM
245
439
0
16 May 2022
Robust Event Classification Using Imperfect Real-world PMU Data
Robust Event Classification Using Imperfect Real-world PMU Data
Yunchuan Liu
Lei Yang
Amir Ghasemkhani
H. Livani
Virgilio Centeno
Pin-Yu Chen
Junshan Zhang
93
23
0
19 Oct 2021
Diffusion Models Beat GANs on Image Synthesis
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal
Alex Nichol
163
7,763
0
11 May 2021
Maximum Likelihood Training of Score-Based Diffusion Models
Maximum Likelihood Training of Score-Based Diffusion Models
Yang Song
Conor Durkan
Iain Murray
Stefano Ermon
DiffM
120
657
0
22 Jan 2021
Score-Based Generative Modeling through Stochastic Differential
  Equations
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song
Jascha Narain Sohl-Dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
Ben Poole
DiffM
SyDa
284
6,401
0
26 Nov 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
209
1,835
0
03 Mar 2020
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using
  Generative Models
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei
Maya Kabkab
Rama Chellappa
AAML
GAN
82
1,176
0
17 May 2018
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
207
8,533
0
16 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
517
5,885
0
08 Jul 2016
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