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ORCIDSebastian Lapuschkin
Person information
- affiliation: Fraunhofer Heinrich Hertz Institute, Berlin, Germany
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2020 – today
- 2022
[j9]Djordje Slijepcevic, Fabian Horst, Sebastian Lapuschkin, Brian Horsak
, Anna-Maria Raberger, Andreas Kranzl, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer:
Explaining Machine Learning Models for Clinical Gait Analysis. ACM Trans. Comput. Heal. 3(2): 14:1-14:27 (2022)- [j8]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Explain and improve: LRP-inference fine-tuning for image captioning models. Inf. Fusion 77: 233-246 (2022) - [j7]Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. Inf. Fusion 77: 261-295 (2022) - [i31]Frederik Pahde, Leander Weber, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin:
PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging. CoRR abs/2202.03482 (2022) - [i30]Franz Motzkus, Leander Weber, Sebastian Lapuschkin:
Measurably Stronger Explanation Reliability via Model Canonization. CoRR abs/2202.06621 (2022) - [i29]Anna Hedström, Leander Weber, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations. CoRR abs/2202.06861 (2022) - [i28]Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement. CoRR abs/2203.08008 (2022) - [i27]Michael Gerstenberger, Sebastian Lapuschkin, Peter Eisert, Sebastian Bosse:
But that's not why: Inference adjustment by interactive prototype deselection. CoRR abs/2203.10087 (2022) - [i26]Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin:
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI. CoRR abs/2205.01929 (2022) - [i25]Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation. CoRR abs/2206.03208 (2022) - 2021
- [j6]Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller:
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109(3): 247-278 (2021) - [j5]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. 115: 107899 (2021) - [i24]Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. CoRR abs/2106.13200 (2021) - [i23]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. CoRR abs/2109.04236 (2021) - 2020
- [c9]Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin:
ECQ x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. xxAI@ICML 2020: 271-296 - [c8]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. ICPR 2020: 4949-4956 - [c7]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. ICPR 2020: 7609-7616 - [c6]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards Best Practice in Explaining Neural Network Decisions with LRP. IJCNN 2020: 1-7 - [i22]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Understanding Image Captioning Models beyond Visualizing Attention. CoRR abs/2001.01037 (2020) - [i21]Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller:
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR abs/2003.07631 (2020) - [i20]Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder:
Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. CoRR abs/2004.10484 (2020) - [i19]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder:
Explanation-Guided Training for Cross-Domain Few-Shot Classification. CoRR abs/2007.08790 (2020)
2010 – 2019
- 2019
- [b1]Sebastian Lapuschkin:
Opening the machine learning black box with Layer-wise Relevance Propagation. Technical University of Berlin, Germany, 2019 - [j4]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate Neural Networks! J. Mach. Learn. Res. 20: 93:1-93:8 (2019) - [p1]Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller:
Layer-Wise Relevance Propagation: An Overview. Explainable AI 2019: 193-209 - [i18]Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller:
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. CoRR abs/1902.10178 (2019) - [i17]Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder:
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. CoRR abs/1908.06943 (2019) - [i16]Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Towards best practice in explaining neural network decisions with LRP. CoRR abs/1910.09840 (2019) - [i15]Fabian Horst, Djordje Slijepcevic, Sebastian Lapuschkin, Anna-Maria Raberger, Matthias Zeppelzauer, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Brian Horsak:
On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence. CoRR abs/1912.07737 (2019) - [i14]Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. CoRR abs/1912.08881 (2019) - [i13]Christopher J. Anders, Talmaj Marinc, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin:
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. CoRR abs/1912.11425 (2019) - 2018
- [i12]Sören Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals. CoRR abs/1807.03418 (2018) - [i11]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate neural networks! CoRR abs/1808.04260 (2018) - [i10]Fabian Horst, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller, Wolfgang Immanuel Schöllhorn:
What is Unique in Individual Gait Patterns? Understanding and Interpreting Deep Learning in Gait Analysis. CoRR abs/1808.04308 (2018) - 2017
- [j3]Grégoire Montavon, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining nonlinear classification decisions with deep Taylor decomposition. Pattern Recognit. 65: 211-222 (2017) - [j2]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller:
Evaluating the Visualization of What a Deep Neural Network Has Learned. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2660-2673 (2017) - [c5]Vignesh Srinivasan, Sebastian Lapuschkin, Cornelius Hellge, Klaus-Robert Müller, Wojciech Samek:
Interpretable human action recognition in compressed domain. ICASSP 2017: 1692-1696 - [c4]Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. ICCV Workshops 2017: 1629-1638 - [i9]Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Understanding and Comparing Deep Neural Networks for Age and Gender Classification. CoRR abs/1708.07689 (2017) - 2016
- [j1]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
The LRP Toolbox for Artificial Neural Networks. J. Mach. Learn. Res. 17: 114:1-114:5 (2016) - [c3]Sebastian Lapuschkin, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR 2016: 2912-2920 - [c2]Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek:
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN (2) 2016: 63-71 - [c1]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling explanatory heatmap resolution and semantics via decomposition depth. ICIP 2016: 2271-2275 - [i8]Sebastian Bach, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
Controlling Explanatory Heatmap Resolution and Semantics via Decomposition Depth. CoRR abs/1603.06463 (2016) - [i7]Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller, Wojciech Samek:
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers. CoRR abs/1604.00825 (2016) - [i6]Irene Sturm, Sebastian Bach, Wojciech Samek, Klaus-Robert Müller:
Interpretable Deep Neural Networks for Single-Trial EEG Classification. CoRR abs/1604.08201 (2016) - [i5]Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller:
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. CoRR abs/1611.08191 (2016) - 2015
- [i4]Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, Klaus-Robert Müller:
Evaluating the visualization of what a Deep Neural Network has learned. CoRR abs/1509.06321 (2015) - [i3]Sebastian Bach, Alexander Binder, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CoRR abs/1512.00172 (2015) - [i2]Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Müller:
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition. CoRR abs/1512.02479 (2015) - 2014
- [i1]Guido Schwenk, Sebastian Bach:
Detecting Behavioral and Structural Anomalies in MediaCloud Applications. CoRR abs/1409.8035 (2014)
Coauthor Index
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