GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization

6 July 2021

Papers citing "GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization"

29 / 29 papers shown

Title
Learning Optimal Prompt Ensemble for Multi-source Visual Prompt Transfer Enming Zhang Liwen Cao Yanru Wu Zijie Zhao Guan Wang Yang Li 52 0 0 09 Apr 2025
Measuring Diversity in Synthetic Datasets Yuchang Zhu Huizhe Zhang Bingzhe Wu Jintang Li Zibin Zheng Peilin Zhao Liang Chen Yatao Bian 100 0 0 12 Feb 2025
Bayesian Optimization with Preference Exploration by Monotonic Neural Network Ensemble Hanyang Wang Juergen Branke Matthias Poloczek 107 0 0 30 Jan 2025
BayesNAM: Leveraging Inconsistency for Reliable Explanations Hoki Kim Jinseong Park Yujin Choi Seungyun Lee Jaewook Lee BDL 29 0 0 10 Nov 2024
Comparative Evaluation of Applicability Domain Definition Methods for Regression Models Shakir Khurshid Bharath Kumar Loganathan Matthieu Duvinage 32 0 0 01 Nov 2024
MIRACLE3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model Construction Hossein Resani B. Nasihatkon 3DV 142 0 0 08 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning Nils Lehmann Jakob Gawlikowski Adam J. Stewart Vytautas Jancauskas Stefan Depeweg Eric T. Nalisnick N. Gottschling 42 0 0 04 Oct 2024
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model Yuanpu Cao Lu Lin Jinghui Chen DiffM 26 1 0 09 Aug 2024
Improving Adversarial Robustness via Decoupled Visual Representation Masking Decheng Liu Tao Chen Chunlei Peng Nannan Wang Ruimin Hu Xinbo Gao AAML 51 1 0 16 Jun 2024
Learning from Uncertain Data: From Possible Worlds to Possible Models Jiongli Zhu Su Feng Boris Glavic Babak Salimi 37 0 0 28 May 2024
Boosting Model Resilience via Implicit Adversarial Data Augmentation Xiaoling Zhou Wei Ye Zhemg Lee Rui Xie Shi-Bo Zhang 44 1 0 25 Apr 2024
Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks Youngkyoung Bae Seungwoong Ha Hawoong Jeong 73 2 0 02 Feb 2024
BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks Meixi Zheng Xuanchen Yan Zihao Zhu Hongrui Chen Baoyuan Wu ELM MLAU AAML 34 8 0 28 Dec 2023
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks Seokil Ham Jun-Gyu Park Dong-Jun Han Jaekyun Moon AAML 16 4 0 01 Nov 2023
Data Optimization in Deep Learning: A Survey Ou Wu Rujing Yao 38 1 0 25 Oct 2023
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference Dejan Porjazovski Yaroslav Getman Tamás Grósz M. Kurimo 30 3 0 16 Oct 2023
On Continuity of Robust and Accurate Classifiers R. Barati Reza Safabakhsh Mohammad Rahmati AAML 10 1 0 29 Sep 2023
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 25 43 0 17 Jun 2023
Uncertainty Aware Neural Network from Similarity and Sensitivity H. M. D. Kabir S. Mondal Sadia Khanam Abbas Khosravi Shafin Rahman ... R. Alizadehsani Houshyar Asadi Shady M. K. Mohamed Saeid Nahavandi Usha R. Acharya AAML 28 4 0 27 Apr 2023
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing M. Hasan Moloud Abdar Abbas Khosravi U. Aickelin Pietro Lio Ibrahim Hossain Ashikur Rahman Saeid Nahavandi 35 4 0 11 Apr 2023
On the role of Model Uncertainties in Bayesian Optimization Jonathan Foldager Mikkel Jordahn Lars Kai Hansen Michael Riis Andersen 19 4 0 14 Jan 2023
Ares: A System-Oriented Wargame Framework for Adversarial ML Farhan Ahmed Pratik Vaishnavi Kevin Eykholt Amir Rahmati AAML 23 7 0 24 Oct 2022
BayesNetCNN: incorporating uncertainty in neural networks for image-based classification tasks Matteo Ferrante T. Boccato N. Toschi BDL UQCV 11 0 0 27 Sep 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape Panagiotis Eustratiadis Henry Gouk Da Li Timothy M. Hospedales AAML 22 4 0 01 Aug 2022
Gradient Obfuscation Checklist Test Gives a False Sense of Security Nikola Popovic D. Paudel Thomas Probst Luc Van Gool AAML 36 6 0 03 Jun 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Daubener Asja Fischer SILM AAML 20 1 0 22 Apr 2022
Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers Nikola Popovic D. Paudel Thomas Probst Luc Van Gool 34 1 0 30 Dec 2021
The art of defense: letting networks fool the attacker Jinlai Zhang Lyvjie Chen Binbin Liu Bojun Ouyang Jihong Zhu Minchi Kuang Houqing Wang Yanmei Meng AAML 3DPC 17 15 0 07 Apr 2021
Determinantal point processes for machine learning Alex Kulesza B. Taskar 162 1,123 0 25 Jul 2012