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1710.10547
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Interpretation of Neural Networks is Fragile
AAAI Conference on Artificial Intelligence (AAAI), 2017
29 October 2017
Amirata Ghorbani
Abubakar Abid
James Zou
FAtt
AAML
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Papers citing
"Interpretation of Neural Networks is Fragile"
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The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Conference on Fairness, Accountability and Transparency (FAccT), 2022
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Haoran Zhang
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Thomas Hartvigsen
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Marzyeh Ghassemi
276
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06 May 2022
ExSum: From Local Explanations to Model Understanding
North American Chapter of the Association for Computational Linguistics (NAACL), 2022
Yilun Zhou
Marco Tulio Ribeiro
J. Shah
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30 Apr 2022
Poly-CAM: High resolution class activation map for convolutional neural networks
Machine Vision and Applications (MVA), 2022
A. Englebert
O. Cornu
Christophe De Vleeschouwer
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28 Apr 2022
It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers
International Conference on Computational Logic (ICCL), 2022
Zheng Tang
Mihai Surdeanu
439
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25 Apr 2022
Backdooring Explainable Machine Learning
Maximilian Noppel
Lukas Peter
Christian Wressnegger
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201
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20 Apr 2022
A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation
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Shahin Tajik
F. Ganji
D. Woodard
Domenic Forte
221
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19 Apr 2022
Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention
Computer Vision and Pattern Recognition (CVPR), 2022
Yu Yang
Seung Wook Kim
Jungseock Joo
FAtt
187
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10 Apr 2022
Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Models
European Journal of Operational Research (EJOR), 2022
Alexander Stevens
Johannes De Smedt
XAI
FaML
523
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30 Mar 2022
Interpretable Prediction of Pulmonary Hypertension in Newborns using Echocardiograms
German Conference on Pattern Recognition (GCPR), 2022
H. Ragnarsdóttir
Laura Manduchi
H. Michel
F. Laumer
S. Wellmann
Ece Ozkan
Julia-Franziska Vogt
174
3
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24 Mar 2022
Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation
AAAI Conference on Artificial Intelligence (AAAI), 2022
Hanjie Chen
Yangfeng Ji
OOD
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221
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23 Mar 2022
Rethinking Stability for Attribution-based Explanations
Chirag Agarwal
Nari Johnson
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199
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14 Mar 2022
Explaining Classifiers by Constructing Familiar Concepts
Machine-mediated learning (ML), 2022
Johannes Schneider
M. Vlachos
187
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07 Mar 2022
Concept-based Explanations for Out-Of-Distribution Detectors
International Conference on Machine Learning (ICML), 2022
Jihye Choi
Jayaram Raghuram
Ryan Feng
Jiefeng Chen
S. Jha
Atul Prakash
OODD
201
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04 Mar 2022
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths
Amir Hossein Akhavan Rahnama
Judith Butepage
XAI
FAtt
109
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04 Mar 2022
Evaluating Feature Attribution Methods in the Image Domain
Machine-mediated learning (ML), 2022
Arne Gevaert
Axel-Jan Rousseau
Thijs Becker
D. Valkenborg
T. D. Bie
Yvan Saeys
FAtt
137
27
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22 Feb 2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis
Computer Vision and Pattern Recognition (CVPR), 2022
Thomas Fel
Mélanie Ducoffe
David Vigouroux
Rémi Cadène
Mikael Capelle
C. Nicodeme
Thomas Serre
AAML
243
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15 Feb 2022
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
Himabindu Lakkaraju
Dylan Slack
Yuxin Chen
Chenhao Tan
Sameer Singh
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217
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03 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna
Tessa Han
Alex Gu
Steven Wu
S. Jabbari
Himabindu Lakkaraju
744
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03 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning
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Mariella Dimiccoli
Brian Y. Lim
FAtt
205
1
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30 Jan 2022
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
Neural Information Processing Systems (NeurIPS), 2022
Amit Dhurandhar
Karthikeyan N. Ramamurthy
Kartik Ahuja
Vijay Arya
FAtt
228
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0
28 Jan 2022
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
Conference on Fairness, Accountability and Transparency (FAccT), 2022
Alon Jacovi
Jasmijn Bastings
Sebastian Gehrmann
Yoav Goldberg
Katja Filippova
443
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27 Jan 2022
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes
Computer Vision and Pattern Recognition (CVPR), 2022
Mazda Moayeri
Phillip E. Pope
Yogesh Balaji
Soheil Feizi
VLM
214
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26 Jan 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
ACM Computing Surveys (ACM CSUR), 2022
Meike Nauta
Jan Trienes
Shreyasi Pathak
Elisa Nguyen
Michelle Peters
Yasmin Schmitt
Jorg Schlotterer
M. V. Keulen
C. Seifert
ELM
XAI
583
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20 Jan 2022
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank Metrics
International Journal of Information Security (JIS), 2022
Haya Brama
L. Dery
Tal Grinshpoun
AAML
164
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10 Jan 2022
Topological Representations of Local Explanations
Peter Xenopoulos
G. Chan
Harish Doraiswamy
L. G. Nonato
Brian Barr
Claudio Silva
FAtt
181
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06 Jan 2022
GPEX, A Framework For Interpreting Artificial Neural Networks
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Amir Akbarnejad
G. Bigras
Nilanjan Ray
188
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18 Dec 2021
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Wenjie Shi
Gao Huang
Shiji Song
Cheng Wu
167
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06 Dec 2021
Multi-objective Explanations of GNN Predictions
Yifei Liu
Chao Chen
Yazheng Liu
Xi Zhang
Sihong Xie
197
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29 Nov 2021
Improving Deep Learning Interpretability by Saliency Guided Training
Neural Information Processing Systems (NeurIPS), 2021
Aya Abdelsalam Ismail
H. C. Bravo
Soheil Feizi
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225
102
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29 Nov 2021
Selective Ensembles for Consistent Predictions
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Emily Black
Klas Leino
Matt Fredrikson
134
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16 Nov 2021
Statistical Perspectives on Reliability of Artificial Intelligence Systems
Yili Hong
J. Lian
Li Xu
Jie Min
Yueyao Wang
Laura J. Freeman
Xinwei Deng
162
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09 Nov 2021
Defense Against Explanation Manipulation
Ruixiang Tang
Ninghao Liu
Fan Yang
Na Zou
Helen Zhou
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154
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08 Nov 2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis
Thomas Fel
Rémi Cadène
Mathieu Chalvidal
Matthieu Cord
David Vigouroux
Thomas Serre
MLAU
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263
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07 Nov 2021
Callee: Recovering Call Graphs for Binaries with Transfer and Contrastive Learning
IEEE Symposium on Security and Privacy (IEEE S&P), 2021
Wenyu Zhu
Zhiyao Feng
Zihan Zhang
Jian-jun Chen
Zhijian Ou
Min Yang
Chao Zhang
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220
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02 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
Zohaib Salahuddin
Henry C. Woodruff
A. Chatterjee
Philippe Lambin
227
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01 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
Saumitra Mishra
Sanghamitra Dutta
Jason Long
Daniele Magazzeni
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248
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30 Oct 2021
On the explainability of hospitalization prediction on a large COVID-19 patient dataset
American Medical Informatics Association Annual Symposium (AMIA), 2021
Ivan Girardi
P. Vagenas
Dario Arcos-Díaz
Lydia Bessaï
Alexandra Büsser
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R. Furlan
Mauro Gatti
Andrea Giovannini
Ellen Hoeven
Chiara Marchiori
FAtt
80
3
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28 Oct 2021
Provably Robust Model-Centric Explanations for Critical Decision-Making
Cecilia G. Morales
Nick Gisolfi
R. Edman
J. K. Miller
A. Dubrawski
63
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26 Oct 2021
Coalitional Bayesian Autoencoders -- Towards explainable unsupervised deep learning
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Alexandra Brintrup
145
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The Irrationality of Neural Rationale Models
Yiming Zheng
Serena Booth
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Yilun Zhou
356
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Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools
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CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq
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M. Thomson
Meena Subramaniam
Richard K. Perez
Chun Jimmie Ye
J. Zou
41
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13 Oct 2021
Implicit Bias of Linear Equivariant Networks
International Conference on Machine Learning (ICML), 2021
Hannah Lawrence
Kristian Georgiev
A. Dienes
B. Kiani
AI4CE
216
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0
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Consistent Counterfactuals for Deep Models
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Zifan Wang
Matt Fredrikson
Anupam Datta
BDL
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157
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NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks
F. Siciliano
Maria Sofia Bucarelli
Gabriele Tolomei
Fabrizio Silvestri
GNN
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AdjointBackMapV2: Precise Reconstruction of Arbitrary CNN Unit's Activation via Adjoint Operators
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Siu Wun Cheung
Yoonsuck Choe
183
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Trustworthy AI: From Principles to Practices
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Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
471
513
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Adversarial Regression with Doubly Non-negative Weighting Matrices
Tam Le
Truyen V. Nguyen
M. Yamada
Jose H. Blanchet
Viet Anh Nguyen
213
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Deep neural networks with controlled variable selection for the identification of putative causal genetic variants
P. H. Kassani
Fred Lu
Yann Le Guen
Zihuai He
242
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29 Sep 2021
Discriminative Attribution from Counterfactuals
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A. S. Bates
G. Jefferis
Jan Funke
FAtt
CML
95
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28 Sep 2021
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