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1412.6806
Cited By
Striving for Simplicity: The All Convolutional Net
21 December 2014
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
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Papers citing
"Striving for Simplicity: The All Convolutional Net"
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Title
On The Coherence of Quantitative Evaluation of Visual Explanations
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Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment
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Alfonso Ortega
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Wentao Zhang
Weishi Zheng
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TextShield: Beyond Successfully Detecting Adversarial Sentences in Text Classification
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Haiyun Jiang
Ying-Cong Chen
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45
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0
03 Feb 2023
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Qi Chen
Bing Xue
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Open Problems in Applied Deep Learning
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44
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26 Jan 2023
Holistically Explainable Vision Transformers
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Bernt Schiele
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41
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0
20 Jan 2023
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Hanwei Zhang
Felipe Torres
R. Sicre
Yannis Avrithis
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41
22
0
17 Jan 2023
Rationalizing Predictions by Adversarial Information Calibration
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Thomas Lukasiewicz
27
4
0
15 Jan 2023
Modulation spectral features for speech emotion recognition using deep neural networks
Premjeet Singh
Md. Sahidullah
G. Saha
29
44
0
14 Jan 2023
Efficient Activation Function Optimization through Surrogate Modeling
G. Bingham
Risto Miikkulainen
24
2
0
13 Jan 2023
Explainability and Robustness of Deep Visual Classification Models
Jindong Gu
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47
2
0
03 Jan 2023
Deep Hierarchy Quantization Compression algorithm based on Dynamic Sampling
W. Jiang
Gang Liu
Xiaofeng Chen
Yipeng Zhou
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19
0
0
30 Dec 2022
Human Activity Recognition from Wi-Fi CSI Data Using Principal Component-Based Wavelet CNN
I. A. Showmik
Tahsina Farah Sanam
H. Imtiaz
11
13
0
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Explainable AI for Bioinformatics: Methods, Tools, and Applications
Md. Rezaul Karim
Tanhim Islam
Oya Beyan
Christoph Lange
Michael Cochez
Dietrich-Rebholz Schuhmann
Stefan Decker
31
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0
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DExT: Detector Explanation Toolkit
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Paul G. Plöger
Octavio Arriaga
Matias Valdenegro-Toro
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0
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When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study
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Paolo Tonella
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29
0
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Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
Borui Zhang
Wenzhao Zheng
Jie Zhou
Jiwen Lu
AAML
27
7
0
18 Dec 2022
Domain Generalization by Learning and Removing Domain-specific Features
Yuzhu Ding
Lei Wang
Binxin Liang
Shuming Liang
Yang Wang
Fangxiao Chen
OOD
30
41
0
14 Dec 2022
Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods
Ming-Xiu Jiang
Saeed Khorram
Li Fuxin
FAtt
27
9
0
13 Dec 2022
COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data
Jonas C. Ditz
Bernhard Reuter
Nícolas Pfeifer
29
1
0
02 Dec 2022
Optimizing Explanations by Network Canonization and Hyperparameter Search
Frederik Pahde
Galip Umit Yolcu
Alexander Binder
Wojciech Samek
Sebastian Lapuschkin
60
11
0
30 Nov 2022
FedGPO: Heterogeneity-Aware Global Parameter Optimization for Efficient Federated Learning
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Carole-Jean Wu
FedML
27
5
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Interpretations Cannot Be Trusted: Stealthy and Effective Adversarial Perturbations against Interpretable Deep Learning
Eldor Abdukhamidov
Mohammed Abuhamad
Simon S. Woo
Eric Chan-Tin
Tamer Abuhmed
AAML
36
9
0
29 Nov 2022
Towards More Robust Interpretation via Local Gradient Alignment
Sunghwan Joo
Seokhyeon Jeong
Juyeon Heo
Adrian Weller
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38
5
0
29 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review
Kumar Abhishek
Deeksha Kamath
35
18
0
27 Nov 2022
Evaluating Feature Attribution Methods for Electrocardiogram
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Jimyeong Kim
Euna Jung
Wonjong Rhee
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22
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0
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Explaining Image Classifiers with Multiscale Directional Image Representation
Stefan Kolek
Robert Windesheim
Héctor Andrade-Loarca
Gitta Kutyniok
Ron Levie
29
4
0
22 Nov 2022
CRAFT: Concept Recursive Activation FacTorization for Explainability
Thomas Fel
Agustin Picard
Louis Bethune
Thibaut Boissin
David Vigouroux
Julien Colin
Rémi Cadène
Thomas Serre
19
103
0
17 Nov 2022
Parameter-Efficient Transformer with Hybrid Axial-Attention for Medical Image Segmentation
Yiyue Hu
Lei Zhang
Nan Mu
Leijun Liu
ViT
MedIm
22
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0
17 Nov 2022
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine
A. Chaddad
Qizong Lu
Jiali Li
Y. Katib
R. Kateb
C. Tanougast
Ahmed Bouridane
Ahmed Abdulkadir
OOD
26
38
0
17 Nov 2022
Explaining Cross-Domain Recognition with Interpretable Deep Classifier
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Ting Yao
Zhaofan Qiu
Tao Mei
OOD
37
3
0
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What Makes a Good Explanation?: A Harmonized View of Properties of Explanations
Zixi Chen
Varshini Subhash
Marton Havasi
Weiwei Pan
Finale Doshi-Velez
XAI
FAtt
41
18
0
10 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey
Amlan Jyoti
Karthik Balaji Ganesh
Manoj Gayala
Nandita Lakshmi Tunuguntla
Sandesh Kamath
V. Balasubramanian
XAI
FAtt
AAML
34
4
0
09 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark
S. Saifullah
Dominique Mercier
Adriano Lucieri
Andreas Dengel
Sheraz Ahmed
35
14
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Exploring Explainability Methods for Graph Neural Networks
Harsh Patel
Shivam Sahni
14
0
0
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Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data
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C. Lawless
Amy Vincent
Satish Pilla
S. Ramesh
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36
0
0
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HesScale: Scalable Computation of Hessian Diagonals
Mohamed Elsayed
A. R. Mahmood
22
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XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection
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Vahdat Abdelzad
Krzysztof Czarnecki
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Similarity of Neural Architectures using Adversarial Attack Transferability
Jaehui Hwang
Dongyoon Han
Byeongho Heo
Song Park
Sanghyuk Chun
Jong-Seok Lee
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1
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Towards Better Guided Attention and Human Knowledge Insertion in Deep Convolutional Neural Networks
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I. Sintorn
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27
1
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Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching
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Neill D. F. Campbell
FedML
37
1
0
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Toward the application of XAI methods in EEG-based systems
Andrea Apicella
Francesco Isgrò
A. Pollastro
R. Prevete
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AI4TS
27
14
0
12 Oct 2022
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
Tao Yang
Jinghao Deng
Xiaojun Quan
Qifan Wang
Shaoliang Nie
32
3
0
12 Oct 2022
Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors
Federico Baldassarre
Quentin Debard
Gonzalo Fiz Pontiveros
Tri Kurniawan Wijaya
44
4
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Critical Learning Periods for Multisensory Integration in Deep Networks
Michael Kleinman
Alessandro Achille
Stefano Soatto
35
10
0
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Improving Convolutional Neural Networks for Fault Diagnosis by Assimilating Global Features
Saif S. S. Al-Wahaibi
Qiugang Lu
16
2
0
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Causal Proxy Models for Concept-Based Model Explanations
Zhengxuan Wu
Karel DÓosterlinck
Atticus Geiger
Amir Zur
Christopher Potts
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83
35
0
28 Sep 2022
Recipro-CAM: Fast gradient-free visual explanations for convolutional neural networks
Seokhyun Byun
Won-Jo Lee
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39
4
0
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I-SPLIT: Deep Network Interpretability for Split Computing
Federico Cunico
Luigi Capogrosso
Francesco Setti
D. Carra
Franco Fummi
Marco Cristani
37
14
0
23 Sep 2022
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