Wojciech Samek

24.9k total citations · 9 hit papers
136 papers, 11.7k citations indexed

About

Wojciech Samek is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Wojciech Samek has authored 136 papers receiving a total of 11.7k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Artificial Intelligence, 46 papers in Computer Vision and Pattern Recognition and 29 papers in Cognitive Neuroscience. Recurrent topics in Wojciech Samek's work include Explainable Artificial Intelligence (XAI) (30 papers), EEG and Brain-Computer Interfaces (23 papers) and Neural dynamics and brain function (19 papers). Wojciech Samek is often cited by papers focused on Explainable Artificial Intelligence (XAI) (30 papers), EEG and Brain-Computer Interfaces (23 papers) and Neural dynamics and brain function (19 papers). Wojciech Samek collaborates with scholars based in Germany, South Korea and Japan. Wojciech Samek's co-authors include Klaus‐Robert Müller, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Frederick Klauschen, Sebastian Bach, Falk Schwendicke, Joachim Krois, Andrea Vedaldi and Lars Kai Hansen and has published in prestigious journals such as Bioinformatics, PLoS ONE and NeuroImage.

In The Last Decade

Wojciech Samek

130 papers receiving 11.3k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

2015 2.5k citations Grégoire Montavon, Klaus‐Robert Müller et al. profile →
Methods for interpreting and understanding deep neural networks

2017 1.5k citations Grégoire Montavon, Wojciech Samek et al. profile →
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

2019 876 citations Wojciech Samek, Grégoire Montavon et al. profile →
Explaining nonlinear classification decisions with deep Taylor decomposition

2016 788 citations Grégoire Montavon, Sebastian Lapuschkin et al. Pattern Recognition profile →
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

2021 702 citations Wojciech Samek, Grégoire Montavon et al. profile →
Artificial Intelligence in Dentistry: Chances and Challenges

2020 644 citations Wojciech Samek et al. profile →
Evaluating the Visualization of What a Deep Neural Network Has Learned

2016 620 citations Wojciech Samek, Grégoire Montavon et al. IEEE Transactions on Neural Networks and Learning Systems profile →
PTB-XL, a large publicly available electrocardiography dataset

2020 616 citations Patrick Wagner, Nils Strodthoff et al. Scientific Data profile →
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

2024 172 citations Luca Longo, Mario Brčić et al. Information Fusion profile →

Peers

Countries citing papers authored by Wojciech Samek

Since Specialization

Citations

This map shows the geographic impact of Wojciech Samek's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wojciech Samek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wojciech Samek more than expected).

Fields of papers citing papers by Wojciech Samek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wojciech Samek. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wojciech Samek. The network helps show where Wojciech Samek may publish in the future.

Co-authorship network of co-authors of Wojciech Samek

This figure shows the co-authorship network connecting the top 25 collaborators of Wojciech Samek. A scholar is included among the top collaborators of Wojciech Samek based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wojciech Samek. Wojciech Samek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Optimizing Federated Learning by Entropy-Based Client Selection 2025 ·(unknown), Gabriele Steidl, Karsten Müller, Wojciech Samek	0
2	Explainable AI reveals Clever Hans effects in unsupervised learning models 2025 ·Nature Machine Intelligence ·(unknown), (unknown), Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon	2
3	Human-Centric AI: From Explainability and Trustworthiness to Actionable Ethics 2025 ·Fraunhofer-Publica (Fraunhofer-Gesellschaft) ·Jaesik Choi, Bohyung Han, (unknown), (unknown), Chang D. Yoo, Simon S. Woo, Wojciech Samek	0
4	Explainability can foster trust in artificial intelligence in geoscience 2025 ·Nature Geoscience ·Jesper Dramsch, (unknown), Miguel‐Ángel Fernández‐Torres, Andrea Toreti, (unknown), Lorenzo Nava, Saman Ghaffarian, Ximeng Cheng, Jackie Ma, Wojciech Samek, (unknown), (unknown), (unknown), Arthur Hrast Essenfelder	14
5	Explaining predictive uncertainty by exposing second-order effects 2024 ·Pattern Recognition ·(unknown), Sebastian Lapuschkin, Wojciech Samek, Grégoire Montavon	1
6	Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions breakdown → 2024 ·Information Fusion ·Luca Longo, Mario Brčić, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf	172
7	From Clustering to Cluster Explanations via Neural Networks 2022 ·IEEE Transactions on Neural Networks and Learning Systems ·(unknown), (unknown), Lukas Ruff, Grégoire Montavon, Wojciech Samek, Klaus‐Robert Müller	44
8	Causes of Outcome Learning: a causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome 2022 ·International Journal of Epidemiology ·Andreas Rieckmann, Piotr Dworzyński, Leila Arras, Sebastian Lapuschkin, Wojciech Samek, Onyebuchi A. Arah, Naja Hulvej Rod, Claus Thorn Ekstrøm	7
9	Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain 2022 ·NeuroImage ·S. Hofmann, Frauke Beyer, Sebastian Lapuschkin, (unknown), Markus Loeffler, Klaus‐Robert Müller, Arno Villringer, Wojciech Samek, A. Veronica Witte	31
10	Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence 2021 ·Information Fusion ·Andreas Holzinger, Matthias Dehmer, Frank Emmert‐Streib, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurišica, Natalia Díaz-Rodríguez	145
11	CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations 2021 ·Information Fusion ·Leila Arras, (unknown), Wojciech Samek	67
12	UDSMProt: universal deep sequence models for protein classification 2020 ·Bioinformatics ·Nils Strodthoff, Patrick Wagner, Markus Wenzel, Wojciech Samek	123
13	On the Byzantine Robustness of Clustered Federated Learning 2020 ·Fraunhofer-Publica (Fraunhofer-Gesellschaft) ·Felix Sattler, Klaus‐Robert Müller, Thomas Wiegand, Wojciech Samek	104
14	Towards Ground Truth Evaluation of Visual Explanations 2020 ·arXiv (Cornell University) ·(unknown), Leila Arras, Wojciech Samek	5
15	Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements 2020 ·PUBLISSO (German National Library of Medicine) ·Felix Sattler, Jackie Ma, Patrick Wagner, (unknown), Markus Wenzel, (unknown), Wojciech Samek, Klaus‐Robert Müller, Thomas Wiegand	21
16	PTB-XL, a large publicly available electrocardiography dataset breakdown → 2020 ·Scientific Data ·Patrick Wagner, Nils Strodthoff, (unknown), D. Kreiseler, Fatima I. Lunze, Wojciech Samek, Tobias Schaeffter	616
17	Dependent Scalar Quantization For Neural Network Compression 2020 ·Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) ·(unknown), Heiko Schwarz, (unknown), Simon Wiedemann, (unknown), (unknown), Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand	7
18	On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence 2019 ·arXiv (Cornell University) ·Fabian Horst, Djordje Slijepčević, Sebastian Lapuschkin, (unknown), Matthias Zeppelzauer, Wojciech Samek, Christian Breiteneder, Wolfgang I. Schöllhorn, Brian Horsak	5
19	Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models 2017 ·arXiv (Cornell University) ·Wojciech Samek, Thomas Wiegand, Klaus‐Robert Müller	49
20	Investigating effects of different artefact types on motor imagery BCI 2015 ·PubMed ·(unknown), Irene Winkler, Klaus‐Robert Müller, Wojciech Samek	17

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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