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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Holistically Explainable Vision Transformers Moritz D Boehle Mario Fritz Bernt Schiele ViT 41 9 0 20 Jan 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 36 22 0 17 Jan 2023
Modulation spectral features for speech emotion recognition using deep neural networks Premjeet Singh Md. Sahidullah G. Saha 27 44 0 14 Jan 2023
Efficient Activation Function Optimization through Surrogate Modeling G. Bingham Risto Miikkulainen 18 2 0 13 Jan 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 44 2 0 03 Jan 2023
Deep Hierarchy Quantization Compression algorithm based on Dynamic Sampling W. Jiang Gang Liu Xiaofeng Chen Yipeng Zhou FedML 14 0 0 30 Dec 2022
Explainable AI for Bioinformatics: Methods, Tools, and Applications Md. Rezaul Karim Tanhim Islam Oya Beyan Christoph Lange Michael Cochez Dietrich-Rebholz Schuhmann Stefan Decker 29 68 0 25 Dec 2022
DExT: Detector Explanation Toolkit Deepan Padmanabhan Paul G. Plöger Octavio Arriaga Matias Valdenegro-Toro 33 2 0 21 Dec 2022
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study Vincenzo Riccio Paolo Tonella AAML 24 29 0 21 Dec 2022
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 25 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 22 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
FedGPO: Heterogeneity-Aware Global Parameter Optimization for Efficient Federated Learning Young Geun Kim Carole-Jean Wu FedML 22 5 0 30 Nov 2022
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 30 9 0 29 Nov 2022
Towards More Robust Interpretation via Local Gradient Alignment Sunghwan Joo Seokhyeon Jeong Juyeon Heo Adrian Weller Taesup Moon FAtt 33 5 0 29 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 32 18 0 27 Nov 2022
Evaluating Feature Attribution Methods for Electrocardiogram J. Suh Jimyeong Kim Euna Jung Wonjong Rhee FAtt 22 2 0 23 Nov 2022
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 1 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 24 38 0 17 Nov 2022
Explaining Cross-Domain Recognition with Interpretable Deep Classifier Yiheng Zhang Ting Yao Zhaofan Qiu Tao Mei OOD 35 3 0 15 Nov 2022
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 36 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 32 4 0 09 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark S. Saifullah Dominique Mercier Adriano Lucieri Andreas Dengel Sheraz Ahmed 35 14 0 08 Nov 2022
Exploring Explainability Methods for Graph Neural Networks Harsh Patel Shivam Sahni 9 0 0 03 Nov 2022
Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data Atif Khan C. Lawless Amy Vincent Satish Pilla S. Ramesh A. Mcgough 36 0 0 31 Oct 2022
HesScale: Scalable Computation of Hessian Diagonals Mohamed Elsayed A. R. Mahmood 22 7 0 20 Oct 2022
XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection Sunsheng Gu Vahdat Abdelzad Krzysztof Czarnecki 22 1 0 20 Oct 2022
Similarity of Neural Architectures using Adversarial Attack Transferability Jaehui Hwang Dongyoon Han Byeongho Heo Song Park Sanghyuk Chun Jong-Seok Lee AAML 32 1 0 20 Oct 2022
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching Cangxiong Chen Neill D. F. Campbell FedML 34 1 0 20 Oct 2022
Toward the application of XAI methods in EEG-based systems Andrea Apicella Francesco Isgrò A. Pollastro R. Prevete OOD 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 0 07 Oct 2022
Critical Learning Periods for Multisensory Integration in Deep Networks Michael Kleinman Alessandro Achille Stefano Soatto 35 10 0 06 Oct 2022
Improving Convolutional Neural Networks for Fault Diagnosis by Assimilating Global Features Saif S. S. Al-Wahaibi Qiugang Lu 16 2 0 03 Oct 2022
Causal Proxy Models for Concept-Based Model Explanations Zhengxuan Wu Karel DÓosterlinck Atticus Geiger Amir Zur Christopher Potts MILM 83 35 0 28 Sep 2022
Recipro-CAM: Fast gradient-free visual explanations for convolutional neural networks Seokhyun Byun Won-Jo Lee FAtt 39 4 0 28 Sep 2022
I-SPLIT: Deep Network Interpretability for Split Computing Federico Cunico Luigi Capogrosso Francesco Setti D. Carra Franco Fummi Marco Cristani 35 14 0 23 Sep 2022
Review On Deep Learning Technique For Underwater Object Detection Radhwan Adnan Dakhil A. R. Khayeat 19 11 0 21 Sep 2022
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang FedML 29 11 0 19 Sep 2022
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning David Bertoin Adil Zouitine Mehdi Zouitine Emmanuel Rachelson 36 30 0 16 Sep 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 28 90 0 14 Sep 2022
DASH: Visual Analytics for Debiasing Image Classification via User-Driven Synthetic Data Augmentation Bum Chul Kwon Jungsoo Lee Chaeyeon Chung Nyoungwoo Lee Ho-Jin Choi Jaegul Choo 39 10 0 14 Sep 2022
Boosting Robustness Verification of Semantic Feature Neighborhoods Anan Kabaha Dana Drachsler-Cohen AAML 34 6 0 12 Sep 2022
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps Mohammadreza Amirian Friedhelm Schwenker Thilo Stadelmann AAML 21 16 0 24 Aug 2022
Causality-Inspired Taxonomy for Explainable Artificial Intelligence Pedro C. Neto Tiago B. Gonccalves João Ribeiro Pinto W. Silva Ana F. Sequeira Arun Ross Jaime S. Cardoso XAI 36 12 0 19 Aug 2022
Gradient Mask: Lateral Inhibition Mechanism Improves Performance in Artificial Neural Networks Lei Jiang Yongqing Liu Shihai Xiao Yansong Chua 33 0 0 14 Aug 2022
The Weighting Game: Evaluating Quality of Explainability Methods Lassi Raatikainen Esa Rahtu FAtt XAI 34 4 0 12 Aug 2022