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Striving for Simplicity: The All Convolutional Net

21 December 2014

Jost Tobias Springenberg

Alexey Dosovitskiy

Thomas Brox

Martin Riedmiller

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Papers citing "Striving for Simplicity: The All Convolutional Net"

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EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators Lois Orosa Skanda Koppula Yaman Umuroglu Konstantinos Kanellopoulos Juan Gómez Luna Michaela Blott K. Vissers O. Mutlu 82 4 0 04 Feb 2022
Enhanced Behavioral Cloning with Environmental Losses for Self-Driving Vehicles Nelson Fernandez Pinto Thomas Gilles OffRL 27 0 0 04 Feb 2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets Tal Shnitzer Mikhail Yurochkin Kristjan Greenewald Justin Solomon 97 6 0 03 Feb 2022
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Architecture Matters in Continual Learning Seyed Iman Mirzadeh Arslan Chaudhry Dong Yin Timothy Nguyen Razvan Pascanu Dilan Görür Mehrdad Farajtabar OOD KELM 170 62 0 01 Feb 2022
Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Data Soroor Shekarizadeh R. Rastgoo Saif M. Al-Kuwari Mohammad Sabokrou 40 2 0 31 Jan 2022
LAP: An Attention-Based Module for Concept Based Self-Interpretation and Knowledge Injection in Convolutional Neural Networks Rassa Ghavami Modegh Ahmadali Salimi Alireza Dizaji Hamid R. Rabiee FAtt 67 0 0 27 Jan 2022
Fast Server Learning Rate Tuning for Coded Federated Dropout Giacomo Verardo Daniela F. Barreira Marco Chiesa Dejan Kostic Gerald Q. Maguire Jr FedML 55 1 0 26 Jan 2022
Deeply Explain CNN via Hierarchical Decomposition Mingg-Ming Cheng Peng-Tao Jiang Linghao Han Liang Wang Philip Torr FAtt 96 15 0 23 Jan 2022
Semi-Supervised Adversarial Recognition of Refined Window Structures for Inverse Procedural Façade Modeling Han Hu Xinrong Liang Yulin Ding Qisen Shang Bo Xu X. Ge Min Chen Ruofei Zhong Qing Zhu 67 9 0 22 Jan 2022
Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework Junpeng Wang Liang Wang Yan Zheng Chin-Chia Michael Yeh Shubham Jain Wei Zhang FAtt 89 14 0 19 Jan 2022
Zero-Shot Machine Unlearning Vikram S Chundawat Ayush K Tarun Murari Mandal Mohan S. Kankanhalli MU 104 128 0 14 Jan 2022
Black-box Safety Analysis and Retraining of DNNs based on Feature Extraction and Clustering M. Attaoui Hazem M. Fahmy F. Pastore Lionel C. Briand AAML 67 21 0 13 Jan 2022
Negative Evidence Matters in Interpretable Histology Image Classification Soufiane Belharbi M. Pedersoli Ismail Ben Ayed Luke McCaffrey Eric Granger 107 12 0 07 Jan 2022
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Predicting Peak Stresses In Microstructured Materials Using Convolutional Encoder-Decoder Learning A. Shrivastava Jingxiao Liu K. Dayal Hae Young Noh 55 7 0 03 Jan 2022
Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI Erico Tjoa Hong Jing Khok Tushar Chouhan G. Cuntai FAtt 74 4 0 30 Dec 2021
Forward Composition Propagation for Explainable Neural Reasoning Isel Grau Gonzalo Nápoles M. Bello Yamisleydi Salgueiro A. Jastrzębska 53 1 0 23 Dec 2021
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review F. Giuste Wenqi Shi Yuanda Zhu Tarun Naren Monica Isgut Ying Sha L. Tong Mitali S. Gupte May D. Wang 109 74 0 23 Dec 2021
Reflash Dropout in Image Super-Resolution Xiangtao Kong Xina Liu Jinjin Gu Yu Qiao Chao Dong UQCV 92 59 0 22 Dec 2021
Looking Beyond Corners: Contrastive Learning of Visual Representations for Keypoint Detection and Description Extraction Henrique Siqueira Patrick Ruhkamp Ibrahim Halfaoui Markus Karmann O. Urfalioglu SSL 101 1 0 22 Dec 2021
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions Shahin Atakishiyev Mohammad Salameh Hengshuai Yao Randy Goebel 97 137 0 21 Dec 2021
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 95 66 0 21 Dec 2021
RELAX: Representation Learning Explainability Kristoffer Wickstrøm Daniel J. Trosten Sigurd Løkse Ahcène Boubekki Karl Øyvind Mikalsen Michael C. Kampffmeyer Robert Jenssen FAtt 51 15 0 19 Dec 2021
Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers Zunlei Feng Jiacong Hu Sai Wu Xiaotian Yu Mingli Song Xiuming Zhang 76 14 0 09 Dec 2021
Latent Space Explanation by Intervention Itai Gat Guy Lorberbom Idan Schwartz Tamir Hazan BDL 53 14 0 09 Dec 2021
Evaluating saliency methods on artificial data with different background types Céline Budding Fabian Eitel K. Ritter Stefan Haufe XAI FAtt MedIm 75 5 0 09 Dec 2021
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods Julien Colin Thomas Fel Rémi Cadène Thomas Serre 87 104 0 06 Dec 2021
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 120 58 0 05 Dec 2021
Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition Andrey Kuehlkamp Aidan Boyd A. Czajka Kevin W. Bowyer Patrick Flynn D. Chute Eric Benjamin CVBM 132 10 0 01 Dec 2021
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Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes Jonathan Donnelly A. Barnett Chaofan Chen 3DH 132 130 0 29 Nov 2021
Reinforcement Explanation Learning Siddhant Agarwal Owais Iqbal Sree Aditya Buridi Madda Manjusha Abir Das FAtt 31 0 0 26 Nov 2021
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley GAN 103 12 0 26 Nov 2021
Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN Wen Yu Baiying Lei Yanyan Shen Shuqiang Wang Yong Liu Z. Feng Yong Hu Michael K. Ng GAN MedIm 54 85 0 25 Nov 2021
Unity is strength: Improving the Detection of Adversarial Examples with Ensemble Approaches Francesco Craighero Fabrizio Angaroni Fabio Stella Chiara Damiani M. Antoniotti Alex Graudenzi AAML 55 8 0 24 Nov 2021
Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes Utku Ozbulak Maura Pintor Arnout Van Messem W. D. Neve AAML 46 5 0 22 Nov 2021
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification Cangxiong Chen Neill D. F. Campbell FedML 68 24 0 19 Nov 2021
Fast Yet Effective Machine Unlearning Ayush K Tarun Vikram S Chundawat Murari Mandal Mohan S. Kankanhalli MU 147 188 0 17 Nov 2021
Three-body renormalization group limit cycles based on unsupervised feature learning Bastian Kaspschak U. Meissner DRL 13 3 0 15 Nov 2021
Scrutinizing XAI using linear ground-truth data with suppressor variables Rick Wilming Céline Budding K. Müller Stefan Haufe FAtt 56 26 0 14 Nov 2021
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines V. Borisov Johannes Meier J. V. D. Heuvel Hamed Jalali Gjergji Kasneci FAtt 67 5 0 14 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 72 23 0 09 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 FAtt AAML 170 65 0 07 Nov 2021
Explainable Deep Reinforcement Learning for Portfolio Management: An Empirical Approach Mao Guan Xiao-Yang Liu AIFin AI4TS 51 21 0 07 Nov 2021
Explaining neural network predictions of material strength Ian Palmer T. Nathan Mundhenk B. J. Gallagher Yong Han 48 2 0 05 Nov 2021
Gradient Frequency Modulation for Visually Explaining Video Understanding Models Xinmiao Lin Wentao Bao Matthew Wright Yu Kong FAtt AAML 73 2 0 01 Nov 2021
Mixture Proportion Estimation and PU Learning: A Modern Approach Saurabh Garg Yifan Wu Alexander J. Smola Sivaraman Balakrishnan Zachary Chase Lipton 69 53 0 01 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 85 321 0 01 Nov 2021