Alexander Binder
Alexander Binder
Chair Computer Vision, OvGU, Magdeburg, Germany
Verified email at
Cited by
Cited by
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
S Bach, A Binder, G Montavon, F Klauschen, KR Müller, W Samek
PLoS ONE doi: 10.1371/journal.pone.0130140, 2015
Deep one-class classification
L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ...
International Conference on Machine Learning, 4393-4402, 2018
Explaining nonlinear classification decisions with deep taylor decomposition
G Montavon, S Lapuschkin, A Binder, W Samek, KR Müller
Pattern Recognition 65, 211-222, 2017
Evaluating the visualization of what a deep neural network has learned
W Samek, A Binder, G Montavon, S Lapuschkin, KR Müller
IEEE transactions on neural networks and learning systems, 2017
Unmasking Clever Hans predictors and assessing what machines really learn
S Lapuschkin, S Wäldchen, A Binder, G Montavon, W Samek, KR Müller
Nature Communications 10 (1), 1096, 2019
Layer-wise relevance propagation: an overview
G Montavon, A Binder, S Lapuschkin, W Samek, KR Müller
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 193-209, 2019
Deep Semi-Supervised Anomaly Detection
L Ruff, RA Vandermeulen, N Görnitz, A Binder, E Müller, KR Müller, ...
arXiv preprint arXiv:1906.02694, 2019
Layer-wise relevance propagation for neural networks with local renormalization layers
A Binder, G Montavon, S Lapuschkin, KR Müller, W Samek
International Conference on Artificial Neural Networks, 63-71, 2016
The SHOGUN machine learning toolbox
S Sonnenburg, G Rätsch, S Henschel, C Widmer, J Behr, A Zien, F Bona, ...
The Journal of Machine Learning Research 11, 1799-1802, 2010
Analyzing classifiers: fisher vectors and deep neural networks
S Lapuschkin, A Binder, G Montavon, KR Muller, W Samek
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Pruning by explaining: A novel criterion for deep neural network pruning
SK Yeom, P Seegerer, S Lapuschkin, A Binder, S Wiedemann, KR Müller, ...
Pattern Recognition, 107899, 2021
Layer-wise Relevance Propagation for Deep Neural Network Architectures
A Binder, S Bach, G Montavon, KR Müller, W Samek
Information Science and Applications (ICISA) 2016, 2016
The LRP toolbox for artificial neural networks
S Lapuschkin, A Binder, G Montavon, KR Müller, W Samek
Journal of Machine Learning Research 17 (114), 1-5, 2016
Understanding and Comparing Deep Neural Networks for Age and Gender Classification
S Lapuschkin, A Binder, KR Müller, W Samek
of the IEEE Conference on Computer Vision and Pattern Recognition, 1629-1638, 2017
Towards best practice in explaining neural network decisions with LRP
M Kohlbrenner, A Bauer, S Nakajima, A Binder, W Samek, S Lapuschkin
2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020
Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
F Klauschen, KR Müller, A Binder, M Bockmayr, M Hägele, P Seegerer, ...
Seminars in cancer biology 52, 151-157, 2018
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
M Hägele, P Seegerer, S Lapuschkin, M Bockmayr, W Samek, ...
Scientific Reports 10 (1), 1-12, 2020
Morphological and molecular breast cancer profiling through explainable machine learning
A Binder, M Bockmayr, M Hägele, S Wienert, D Heim, K Hellweg, M Ishii, ...
Nature Machine Intelligence 3 (4), 355-366, 2021
DeepClue: Visual Interpretation of Text-based Deep Stock Prediction
L Shi, Z Teng, L Wang, Y Zhang, A Binder
IEEE Transactions on Knowledge and Data Engineering, 2018
Explanation-guided training for cross-domain few-shot classification
J Sun, S Lapuschkin, W Samek, Y Zhao, NM Cheung, A Binder
2020 25th International Conference on Pattern Recognition (ICPR), 7609-7616, 2021
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