Alexander Binder
Universitetet i Oslo
H-index: 32
Europe-Norway
Top articles of Alexander Binder
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations | Alexander Binder Leander Weber Sebastian Lapuschkin Grégoire Montavon Klaus-Robert Müller | 2023 | |
Layer-wise Feedback Propagation | arXiv preprint arXiv:2308.12053 | Leander Weber Jim Berend Alexander Binder Thomas Wiegand Wojciech Samek | 2023/8/23 |
Beyond explaining: Opportunities and challenges of XAI-based model improvement | Leander Weber Sebastian Lapuschkin Alexander Binder Wojciech Samek | 2023/4/1 | |
Supplement to: Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations | Alexander Binder Leander Weber Sebastian Lapuschkin | 2023/3 | |
Optimizing Explanations by Network Canonization and Hyperparameter Search | Frederik Pahde Galip Ümit Yolcu Alexander Binder Wojciech Samek Sebastian Lapuschkin | 2023 | |
Discovering Transferable Forensic Features for CNN-generated Images Detection | Keshigeyan Chandrasegaran Ngoc-Trung Tran Alexander Binder Ngai-Man Cheung | 2022/10/23 | |
To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy | Plos one | Vignesh Srinivasan Nils Strodthoff Jackie Ma Alexander Binder Klaus-Robert Müller | 2022/10/18 |
Explanation-guided training for cross-domain few-shot classification | Jiamei Sun Sebastian Lapuschkin Wojciech Samek Yunqing Zhao Ngai-Man Cheung | 2020/7/17 | |
Explain and improve: LRP-inference fine-tuning for image captioning models | Information Fusion | Jiamei Sun Sebastian Lapuschkin Wojciech Samek Alexander Binder | 2022/1/1 |
Understanding integrated gradients with smoothtaylor for deep neural network attribution | Gary SW Goh Sebastian Lapuschkin Leander Weber Wojciech Samek Alexander Binder | 2021/1/10 | |
Morphological and molecular breast cancer profiling through explainable machine learning | Nature Machine Intelligence | Alexander Binder Michael Bockmayr Miriam Hägele Stephan Wienert Daniel Heim | 2021/4 |
Analysing the Adversarial Landscape of Binary Stochastic Networks | Information Science and Applications: Proceedings of ICISA 2020 | Yi Xiang Marcus Tan Yuval Elovici Alexander Binder | 2021 |
Pruning by explaining: A novel criterion for deep neural network pruning | Pattern Recognition | Seul-Ki Yeom Philipp Seegerer Sebastian Lapuschkin Alexander Binder Simon Wiedemann | 2021/2/22 |
Toward Scalable and Unified Example-Based Explanation and Outlier Detection | IEEE Transactions on Image Processing | Penny Chong Ngai-Man Cheung Yuval Elovici Alexander Binder | 2021/11/18 |
Adaptive Noise Injection for Training Stochastic Student Networks from Deterministic Teachers | Yi Xianz Marcus Tan Yuval Elovici Alexander Binder | 2021/1/10 | |
Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples | arXiv preprint arXiv:2110.12357 | Yi Xiang Marcus Tan Penny Chong Jiamei Sun Ngai-Man Cheung Yuval Elovici | 2021/10/24 |
Sideinfnet: A deep neural network for semi-automatic semantic segmentation with side information | Jing Yu Koh Duc Thanh Nguyen Quang-Trung Truong Sai-Kit Yeung Alexander Binder | 2020 | |
Simple and effective prevention of mode collapse in deep one-class classification | Penny Chong Lukas Ruff Marius Kloft Alexander Binder | 2020/7 | |
Towards best practice in explaining neural network decisions with LRP | Maximilian Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek | 2020/7/19 | |
Detection of Adversarial Supports in Few-shot Classifiers Using Self-Similarity and Filtering | arXiv preprint arXiv:2012.06330 | Yi Xiang Marcus Tan Penny Chong Jiamei Sun Ngai-Man Cheung Yuval Elovici | 2020/12/9 |
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