Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning

5 May 2021

Noura Al Moubayed

Papers citing "Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning"

21 / 21 papers shown

Title
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 516 10,591 0 17 Feb 2020
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems Xingjun Ma Yuhao Niu Lin Gu Yisen Wang Yitian Zhao James Bailey Feng Lu MedIm AAML 76 454 0 24 Jul 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 60 101 0 08 Jun 2019
Interpretable and Differentially Private Predictions Frederik Harder Matthias Bauer Mijung Park FAtt 50 53 0 05 Jun 2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Nan Wu Jason Phang Jungkyu Park Yiqiu Shen Zhe Huang ... S. G. Kim Laura Heacock Linda Moy Kyunghyun Cho Krzysztof J. Geras MedIm 47 499 0 20 Mar 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Jeremy Irvin Pranav Rajpurkar M. Ko Yifan Yu Silviana Ciurea-Ilcus ... D. Larson C. Langlotz Bhavik Patel M. Lungren A. Ng 118 2,604 0 21 Jan 2019
Multimodal Machine Learning for Automated ICD Coding Keyang Xu Mike Lam Jingzhi Pang Xin Gao Charlotte Band ... A. Khanna J. Cywinski K. Maheshwari P. Xie Eric Xing 52 109 0 31 Oct 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 192 2,063 0 10 Jul 2018
Adversarial Attacks Against Medical Deep Learning Systems S. G. Finlayson Hyung Won Chung I. Kohane Andrew L. Beam SILM AAML OOD MedIm 59 232 0 15 Apr 2018
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 91 1,097 0 27 Dec 2017
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning Pranav Rajpurkar Jeremy Irvin Kaylie Zhu Brandon Yang Hershel Mehta ... Aarti Bagul C. Langlotz K. Shpanskaya M. Lungren A. Ng LM&MA 87 2,712 0 14 Nov 2017
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles Jiajun Lu Hussein Sibai Evan Fabry David A. Forsyth AAML 88 282 0 12 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 317 12,138 0 19 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,018 0 22 May 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 105 894 0 01 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 408 3,813 0 28 Feb 2017
On Detecting Adversarial Perturbations J. H. Metzen Tim Genewein Volker Fischer Bastian Bischoff AAML 73 950 0 14 Feb 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 800 36,892 0 25 Aug 2016
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism Edward Choi M. T. Bahadori Joshua A. Kulas A. Schuetz Walter F. Stewart Jimeng Sun AI4TS 123 1,248 0 19 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,583 0 16 Aug 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014