SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

50 / 1,161 papers shown

Title
$¶$ ILCRO: Making Importance Landscapes Flat Again Vincent Moens Simiao Yu G. Salimi-Khorshidi 9 0 0 27 Jan 2020
Learning Preference-Based Similarities from Face Images using Siamese Multi-Task CNNs N. Gessert Alexander Schlaefer CVBM 18 1 0 25 Jan 2020
SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation Jesse Sun Fatemeh Darbeha M. Zaidi Bo Wang AAML 19 110 0 21 Jan 2020
An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs Joseph D. Janizek G. Erion A. DeGrave Su-In Lee OOD MedIm 30 29 0 13 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Restricting the Flow: Information Bottlenecks for Attribution Karl Schulz Leon Sixt Federico Tombari Tim Landgraf FAtt 14 182 0 02 Jan 2020
When Explanations Lie: Why Many Modified BP Attributions Fail Leon Sixt Maximilian Granz Tim Landgraf BDL FAtt XAI 13 132 0 20 Dec 2019
Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball Andrew Elliott Stephen Law Chris Russell AAML 12 4 0 19 Dec 2019
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning Akanksha Atrey Kaleigh Clary David D. Jensen FAtt LRM 19 90 0 09 Dec 2019
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness Adam Noack Isaac Ahern Dejing Dou Boyang Albert Li OOD AAML 18 10 0 07 Dec 2019
A Step Towards Exposing Bias in Trained Deep Convolutional Neural Network Models Daniel Omeiza FAtt 16 0 0 03 Dec 2019
Automated Dependence Plots David I. Inouye Liu Leqi Joon Sik Kim Bryon Aragam Pradeep Ravikumar 12 1 0 02 Dec 2019
A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors Edward J. Kim D. Gopinath C. Păsăreanu S. Seshia 10 26 0 01 Dec 2019
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
A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients David Zimmerer Jens Petersen Simon A. A. Kohl Klaus H. Maier-Hein DRL 11 22 0 28 Nov 2019
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey Vanessa Buhrmester David Münch Michael Arens MLAU FaML XAI AAML 21 354 0 27 Nov 2019
Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers Ya Zhao Rui Xu Xinchao Wang Peng Hou Haihong Tang Xiuming Zhang 9 89 0 26 Nov 2019
Efficient Saliency Maps for Explainable AI T. Nathan Mundhenk Barry Y. Chen Gerald Friedland XAI FAtt 21 73 0 26 Nov 2019
Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method Junjie Hu Takayuki Okatani AAML MDE 35 15 0 20 Nov 2019
Signed Input Regularization Saeid Asgari Taghanaki Kumar Abhishek Ghassan Hamarneh AAML 10 1 0 16 Nov 2019
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images H. Pinckaers Bram van Ginneken G. Litjens MedIm 27 94 0 11 Nov 2019
ERASER: A Benchmark to Evaluate Rationalized NLP Models Jay DeYoung Sarthak Jain Nazneen Rajani Eric P. Lehman Caiming Xiong R. Socher Byron C. Wallace 50 627 0 08 Nov 2019
XDeep: An Interpretation Tool for Deep Neural Networks Fan Yang Zijian Zhang Haofan Wang Yuening Li Xia Hu XAI HAI 9 3 0 04 Nov 2019
Leveraging Pretrained Image Classifiers for Language-Based Segmentation David Golub Ahmed El-Kishky Roberto Martín-Martín VLM 14 4 0 03 Nov 2019
Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models L. Brocki N. C. Chung FAtt 28 21 0 29 Oct 2019
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks Aya Abdelsalam Ismail Mohamed K. Gunady L. Pessoa H. C. Bravo S. Feizi AI4TS 25 50 0 27 Oct 2019
CXPlain: Causal Explanations for Model Interpretation under Uncertainty Patrick Schwab W. Karlen FAtt CML 40 205 0 27 Oct 2019
Seeing What a GAN Cannot Generate David Bau Jun-Yan Zhu Jonas Wulff William S. Peebles Hendrik Strobelt Bolei Zhou Antonio Torralba GAN 48 308 0 24 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 39 6,119 0 22 Oct 2019
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 22 148 0 22 Oct 2019
Contextual Prediction Difference Analysis for Explaining Individual Image Classifications Jindong Gu Volker Tresp FAtt 26 8 0 21 Oct 2019
Semantics for Global and Local Interpretation of Deep Neural Networks Jindong Gu Volker Tresp AI4CE 30 14 0 21 Oct 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks Ruth C. Fong Mandela Patrick Andrea Vedaldi AAML 25 411 0 18 Oct 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms Z. Q. Lin M. Shafiee S. Bochkarev Michael St. Jules Xiao Yu Wang A. Wong FAtt 29 80 0 16 Oct 2019
Explaining image classifiers by removing input features using generative models Chirag Agarwal Anh Totti Nguyen FAtt 28 15 0 09 Oct 2019
Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork Yulong Wang Xiaolin Hu Hang Su FAtt 14 1 0 07 Oct 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 25 47 0 05 Oct 2019
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
Oblique Decision Trees from Derivatives of ReLU Networks Guang-He Lee Tommi Jaakkola 30 23 0 30 Sep 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 32 436 0 26 Sep 2019
Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song Kun He Jiadong Lin Liwei Wang J. Hopcroft OOD AAML 6 68 0 23 Sep 2019
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models Eric Wallace Jens Tuyls Junlin Wang Sanjay Subramanian Matt Gardner Sameer Singh MILM 20 137 0 19 Sep 2019
Identifying Pediatric Vascular Anomalies With Deep Learning Justin Chan Sharat Raju Randall Bly J. Perkins Shyamnath Gollakota 30 2 0 16 Sep 2019
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust Arjun Reddy Akula Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 24 18 0 15 Sep 2019
NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks Isaac Ahern Adam Noack Luis Guzman-Nateras Dejing Dou Boyang Albert Li Jun Huan FAtt 11 39 0 10 Sep 2019
Understanding Bias in Machine Learning Jindong Gu Daniela Oelke AI4CE FaML 16 22 0 02 Sep 2019
Saliency Methods for Explaining Adversarial Attacks Jindong Gu Volker Tresp FAtt AAML 8 30 0 22 Aug 2019
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
Free-Lunch Saliency via Attention in Atari Agents Dmitry Nikulin A. Ianina Vladimir Aliev Sergey I. Nikolenko FAtt 20 24 0 07 Aug 2019