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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Feature Visualization in 3D Convolutional Neural Networks Chunpeng Li Ya-tang Li FAtt 23 0 0 12 May 2025
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LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint Qianli Ma Dongrui Liu Qian Chen Linfeng Zhang Jing Shao MoMe 168 0 0 24 Feb 2025
Building Bridges, Not Walls -- Advancing Interpretability by Unifying Feature, Data, and Model Component Attribution Shichang Zhang Tessa Han Usha Bhalla Hima Lakkaraju FAtt 150 0 0 17 Feb 2025
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks Jon Vadillo Roberto Santana J. A. Lozano Marta Z. Kwiatkowska BDL AAML 73 0 0 17 Feb 2025
Explaining 3D Computed Tomography Classifiers with Counterfactuals Joseph Paul Cohen Louis Blankemeier Akshay S. Chaudhari MedIm 176 0 0 11 Feb 2025
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment Harrish Thasarathan Julian Forsyth Thomas Fel M. Kowal Konstantinos G. Derpanis 111 7 0 06 Feb 2025
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B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable Shreyash Arya Sukrut Rao Moritz Bohle Bernt Schiele 68 2 0 28 Jan 2025
Pfungst and Clever Hans: Identifying the unintended cues in a widely used Alzheimer's disease MRI dataset using explainable deep learning C. Tinauer Maximilian Sackl Rudolf Stollberger Stefan Ropele C. Langkammer AAML 40 0 0 27 Jan 2025
Generating visual explanations from deep networks using implicit neural representations Michal Byra Henrik Skibbe GAN FAtt 29 0 0 20 Jan 2025
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics Lukas Klein Carsten T. Lüth U. Schlegel Till J. Bungert Mennatallah El-Assady Paul F. Jäger XAI ELM 42 2 0 03 Jan 2025
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Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwaves Alessandro Lovo Amaury Lancelin Corentin Herbert Freddy Bouchet AI4CE 28 0 0 01 Oct 2024
Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities Chengkun Sun Jinqian Pan Juoli Jin Russell Stevens Terry Jiang Bian Jie Xu 22 0 0 20 Sep 2024
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Towards Certified Unlearning for Deep Neural Networks Binchi Zhang Yushun Dong Tianhao Wang Wenlin Yao MU 64 7 0 01 Aug 2024
On the Evaluation Consistency of Attribution-based Explanations Jiarui Duan Haoling Li Haofei Zhang Hao Jiang Mengqi Xue Li Sun Mingli Song Mingli Song XAI 46 1 0 28 Jul 2024
Don't Fear Peculiar Activation Functions: EUAF and Beyond Qianchao Wang Shijun Zhang Dong Zeng Zhaoheng Xie Hengtao Guo Feng-Lei Fan Tieyong Zeng 42 3 0 12 Jul 2024
Explaining Graph Neural Networks for Node Similarity on Graphs Daniel Daza C. Chu T. Tran Daria Stepanova Michael Cochez Paul T. Groth 36 1 0 10 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 63 1 0 01 Jul 2024
Machine Learning Techniques in Automatic Music Transcription: A Systematic Survey Fatemeh Jamshidi Gary Pike Amit Das Richard Chapman 39 4 0 20 Jun 2024
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CONFINE: Conformal Prediction for Interpretable Neural Networks Linhui Huang S. Lala N. Jha 68 2 0 01 Jun 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution Eslam Zaher Maciej Trzaskowski Quan Nguyen Fred Roosta AAML 29 4 0 16 May 2024
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A Learning Paradigm for Interpretable Gradients Felipe Figueroa Hanwei Zhang R. Sicre Yannis Avrithis Stéphane Ayache FAtt 23 0 0 23 Apr 2024
Machine Unlearning via Null Space Calibration Huiqiang Chen Tianqing Zhu Xin Yu Wanlei Zhou 41 6 0 21 Apr 2024
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training Shizhan Gong Qi Dou Farzan Farnia FAtt 42 2 0 06 Apr 2024
A Peg-in-hole Task Strategy for Holes in Concrete André Yuji Yasutomi Hiroki Mori Tetsuya Ogata 26 15 0 29 Mar 2024
Uncertainty Quantification for Gradient-based Explanations in Neural Networks Mihir Mulye Matias Valdenegro-Toro UQCV FAtt 33 0 0 25 Mar 2024
What Sketch Explainability Really Means for Downstream Tasks Hmrishav Bandyopadhyay Pinaki Nath Chowdhury A. Bhunia Aneeshan Sain Tao Xiang Yi-Zhe Song 30 4 0 14 Mar 2024
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Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape Tiejin Chen Wenwang Huang Linsey Pang Dongsheng Luo Hua Wei OOD 49 0 0 09 Mar 2024
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Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models Hongbin Liu Michael K. Reiter Neil Zhenqiang Gong AAML 38 2 0 22 Feb 2024