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RISE: Randomized Input Sampling for Explanation of Black-box Models

RISE: Randomized Input Sampling for Explanation of Black-box Models

19 June 2018
Vitali Petsiuk
Abir Das
Kate Saenko
    FAtt
ArXivPDFHTML

Papers citing "RISE: Randomized Input Sampling for Explanation of Black-box Models"

50 / 652 papers shown
Title
Don't Explain without Verifying Veracity: An Evaluation of Explainable
  AI with Video Activity Recognition
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition
Mahsan Nourani
Chiradeep Roy
Tahrima Rahman
Eric D. Ragan
Nicholas Ruozzi
Vibhav Gogate
AAML
15
17
0
05 May 2020
A robust algorithm for explaining unreliable machine learning survival
  models using the Kolmogorov-Smirnov bounds
A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds
M. Kovalev
Lev V. Utkin
AAML
35
31
0
05 May 2020
SurvLIME-Inf: A simplified modification of SurvLIME for explanation of
  machine learning survival models
SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models
Lev V. Utkin
M. Kovalev
E. Kasimov
10
10
0
05 May 2020
What-if I ask you to explain: Explaining the effects of perturbations in
  procedural text
What-if I ask you to explain: Explaining the effects of perturbations in procedural text
Dheeraj Rajagopal
Niket Tandon
Bhavana Dalvi
Peter Clarke
Eduard H. Hovy
31
14
0
04 May 2020
Explaining AI-based Decision Support Systems using Concept Localization
  Maps
Explaining AI-based Decision Support Systems using Concept Localization Maps
Adriano Lucieri
Muhammad Naseer Bajwa
Andreas Dengel
Sheraz Ahmed
27
26
0
04 May 2020
Towards Visually Explaining Video Understanding Networks with
  Perturbation
Towards Visually Explaining Video Understanding Networks with Perturbation
Zhenqiang Li
Weimin Wang
Zuoyue Li
Yifei Huang
Yoichi Sato
FAtt
20
3
0
01 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAML
XAI
41
371
0
30 Apr 2020
A Disentangling Invertible Interpretation Network for Explaining Latent
  Representations
A Disentangling Invertible Interpretation Network for Explaining Latent Representations
Patrick Esser
Robin Rombach
Bjorn Ommer
6
86
0
27 Apr 2020
Learning Decision Ensemble using a Graph Neural Network for Comorbidity
  Aware Chest Radiograph Screening
Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening
A. Chakravarty
Tandra Sarkar
N. Ghosh
Ramanathan Sethuraman
Debdoot Sheet
25
12
0
24 Apr 2020
A Systematic Search over Deep Convolutional Neural Network Architectures
  for Screening Chest Radiographs
A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs
Arka Mitra
A. Chakravarty
N. Ghosh
Tandra Sarkar
Ramanathan Sethuraman
Debdoot Sheet
9
9
0
24 Apr 2020
CovidAID: COVID-19 Detection Using Chest X-Ray
CovidAID: COVID-19 Detection Using Chest X-Ray
Arpan Mangal
Surya Kalia
Harish Rajgopal
K. Rangarajan
Vinay P. Namboodiri
Subhashis Banerjee
Chetan Arora
OOD
20
150
0
21 Apr 2020
Games for Fairness and Interpretability
Games for Fairness and Interpretability
Eric Chu
Nabeel Gillani
S. Makini
FaML
12
4
0
20 Apr 2020
Contrastive Examples for Addressing the Tyranny of the Majority
Contrastive Examples for Addressing the Tyranny of the Majority
V. Sharmanska
Lisa Anne Hendricks
Trevor Darrell
Novi Quadrianto
6
29
0
14 Apr 2020
There and Back Again: Revisiting Backpropagation Saliency Methods
There and Back Again: Revisiting Backpropagation Saliency Methods
Sylvestre-Alvise Rebuffi
Ruth C. Fong
Xu Ji
Andrea Vedaldi
FAtt
XAI
17
113
0
06 Apr 2020
Interpreting Medical Image Classifiers by Optimization Based
  Counterfactual Impact Analysis
Interpreting Medical Image Classifiers by Optimization Based Counterfactual Impact Analysis
David Major
Dimitrios Lenis
M. Wimmer
Gert Sluiter
Astrid Berg
Katja Bühler
FAtt
19
12
0
03 Apr 2020
NBDT: Neural-Backed Decision Trees
NBDT: Neural-Backed Decision Trees
Alvin Wan
Lisa Dunlap
Daniel Ho
Jihan Yin
Scott Lee
Henry Jin
Suzanne Petryk
Sarah Adel Bargal
Joseph E. Gonzalez
11
99
0
01 Apr 2020
SurvLIME: A method for explaining machine learning survival models
SurvLIME: A method for explaining machine learning survival models
M. Kovalev
Lev V. Utkin
E. Kasimov
108
89
0
18 Mar 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and
  Applications
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Wojciech Samek
G. Montavon
Sebastian Lapuschkin
Christopher J. Anders
K. Müller
XAI
44
82
0
17 Mar 2020
Explainable Deep Classification Models for Domain Generalization
Explainable Deep Classification Models for Domain Generalization
Andrea Zunino
Sarah Adel Bargal
Riccardo Volpi
M. Sameki
Jianming Zhang
Stan Sclaroff
Vittorio Murino
Kate Saenko
FAtt
16
39
0
13 Mar 2020
SAM: The Sensitivity of Attribution Methods to Hyperparameters
SAM: The Sensitivity of Attribution Methods to Hyperparameters
Naman Bansal
Chirag Agarwal
Anh Nguyen
FAtt
16
0
0
04 Mar 2020
Transformation Importance with Applications to Cosmology
Transformation Importance with Applications to Cosmology
Chandan Singh
Wooseok Ha
F. Lanusse
V. Boehm
Jia-Wei Liu
Bin Yu
AI4CE
22
11
0
04 Mar 2020
Supporting DNN Safety Analysis and Retraining through Heatmap-based
  Unsupervised Learning
Supporting DNN Safety Analysis and Retraining through Heatmap-based Unsupervised Learning
Hazem M. Fahmy
F. Pastore
M. Bagherzadeh
Lionel C. Briand
AI4CE
AAML
43
30
0
03 Feb 2020
Deceptive AI Explanations: Creation and Detection
Deceptive AI Explanations: Creation and Detection
Johannes Schneider
Christian Meske
Michalis Vlachos
19
28
0
21 Jan 2020
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning
  Models
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models
Jiamei Sun
Sebastian Lapuschkin
Wojciech Samek
Alexander Binder
FAtt
42
29
0
04 Jan 2020
Explaining Classifiers using Adversarial Perturbations on the Perceptual
  Ball
Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball
Andrew Elliott
Stephen Law
Chris Russell
AAML
10
4
0
19 Dec 2019
Iterative and Adaptive Sampling with Spatial Attention for Black-Box
  Model Explanations
Iterative and Adaptive Sampling with Spatial Attention for Black-Box Model Explanations
Bhavan Kumar Vasu
Chengjiang Long
FAtt
23
11
0
18 Dec 2019
ViBE: Dressing for Diverse Body Shapes
ViBE: Dressing for Diverse Body Shapes
Wei-Lin Hsiao
Kristen Grauman
3DH
16
36
0
13 Dec 2019
Attributional Robustness Training using Input-Gradient Spatial Alignment
Attributional Robustness Training using Input-Gradient Spatial Alignment
M. Singh
Nupur Kumari
Puneet Mangla
Abhishek Sinha
V. Balasubramanian
Balaji Krishnamurthy
OOD
29
10
0
29 Nov 2019
Improving Feature Attribution through Input-specific Network Pruning
Improving Feature Attribution through Input-specific Network Pruning
Ashkan Khakzar
Soroosh Baselizadeh
Saurabh Khanduja
Christian Rupprecht
S. T. Kim
Nassir Navab
FAtt
6
11
0
25 Nov 2019
Visualizing Point Cloud Classifiers by Curvature Smoothing
Visualizing Point Cloud Classifiers by Curvature Smoothing
Ziwen Chen
Wenxuan Wu
Zhongang Qi
Fuxin Li
3DPC
31
5
0
23 Nov 2019
Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA
Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA
Badri N. Patro
Anupriy
Vinay P. Namboodiri
AAML
FAtt
48
26
0
19 Nov 2019
GRACE: Generating Concise and Informative Contrastive Sample to Explain
  Neural Network Model's Prediction
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction
Thai V. Le
Suhang Wang
Dongwon Lee
13
1
0
05 Nov 2019
Occlusions for Effective Data Augmentation in Image Classification
Occlusions for Effective Data Augmentation in Image Classification
Ruth C. Fong
Andrea Vedaldi
27
20
0
23 Oct 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
Ruth C. Fong
Mandela Patrick
Andrea Vedaldi
AAML
25
411
0
18 Oct 2019
Granular Multimodal Attention Networks for Visual Dialog
Granular Multimodal Attention Networks for Visual Dialog
Badri N. Patro
Shivansh Patel
Vinay P. Namboodiri
33
1
0
13 Oct 2019
Explaining image classifiers by removing input features using generative
  models
Explaining image classifiers by removing input features using generative models
Chirag Agarwal
Anh Totti Nguyen
FAtt
28
15
0
09 Oct 2019
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural
  Networks
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks
Mehdi Neshat
Zifan Wang
Bradley Alexander
Fan Yang
Zijian Zhang
Sirui Ding
Markus Wagner
Xia Hu
FAtt
14
1,049
0
03 Oct 2019
Semantically Interpretable Activation Maps: what-where-how explanations
  within CNNs
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs
Diego Marcos
Sylvain Lobry
D. Tuia
FAtt
MILM
22
26
0
18 Sep 2019
Deep Weakly-Supervised Learning Methods for Classification and
  Localization in Histology Images: A Survey
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey
Jérôme Rony
Soufiane Belharbi
Jose Dolz
Ismail Ben Ayed
Luke McCaffrey
Eric Granger
25
70
0
08 Sep 2019
Interpretable and Fine-Grained Visual Explanations for Convolutional
  Neural Networks
Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks
Jörg Wagner
Jan M. Köhler
Tobias Gindele
Leon Hetzel
Thaddäus Wiedemer
Sven Behnke
AAML
FAtt
21
121
0
07 Aug 2019
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
Pengyi Zhang
Yunxin Zhong
Yulin Deng
Xiaoying Tang
Xiaoqiong Li
22
32
0
01 Aug 2019
Information-Bottleneck Approach to Salient Region Discovery
Information-Bottleneck Approach to Salient Region Discovery
A. Zhmoginov
Ian S. Fischer
Mark Sandler
12
18
0
22 Jul 2019
Weakly Supervised Object Detection with 2D and 3D Regression Neural
  Networks
Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks
Florian Dubost
H. Adams
P. Yilmaz
Gerda Bortsova
Gijs van Tulder
M. Ikram
W. Niessen
Meike W. Vernooij
Marleen de Bruijne
MedIm
10
43
0
05 Jun 2019
SizeNet: Weakly Supervised Learning of Visual Size and Fit in Fashion
  Images
SizeNet: Weakly Supervised Learning of Visual Size and Fit in Fashion Images
Nour Karessli
Romain Guigourès
Reza Shirvany
3DH
24
18
0
28 May 2019
Why do These Match? Explaining the Behavior of Image Similarity Models
Why do These Match? Explaining the Behavior of Image Similarity Models
Bryan A. Plummer
Mariya I. Vasileva
Vitali Petsiuk
Kate Saenko
David A. Forsyth
XAI
FAtt
23
18
0
26 May 2019
Embedding Human Knowledge into Deep Neural Network via Attention Map
Embedding Human Knowledge into Deep Neural Network via Attention Map
Masahiro Mitsuhara
Hiroshi Fukui
Yusuke Sakashita
Takanori Ogata
Tsubasa Hirakawa
Takayoshi Yamashita
H. Fujiyoshi
16
72
0
09 May 2019
Visualizing Deep Networks by Optimizing with Integrated Gradients
Visualizing Deep Networks by Optimizing with Integrated Gradients
Zhongang Qi
Saeed Khorram
Fuxin Li
FAtt
17
122
0
02 May 2019
Interpreting Adversarial Examples by Activation Promotion and
  Suppression
Interpreting Adversarial Examples by Activation Promotion and Suppression
Kaidi Xu
Sijia Liu
Gaoyuan Zhang
Mengshu Sun
Pu Zhao
Quanfu Fan
Chuang Gan
X. Lin
AAML
FAtt
24
43
0
03 Apr 2019
Fooling Neural Network Interpretations via Adversarial Model
  Manipulation
Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo
Sunghwan Joo
Taesup Moon
AAML
FAtt
18
201
0
06 Feb 2019
Learning Decision Trees Recurrently Through Communication
Learning Decision Trees Recurrently Through Communication
Stephan Alaniz
Diego Marcos
Bernt Schiele
Zeynep Akata
30
16
0
05 Feb 2019
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