World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
34490
World Ranking
2138
National Ranking
90

Overview

Wojciech Samek is affiliated with the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute in Germany. Their research is primarily situated within the field of Computer Science, with a strong emphasis on Artificial Intelligence, contributing to 214 publications in this subfield. Additional areas of research include Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Health Informatics, and Cognitive Neuroscience.

The scientist's work spans several topics within machine learning and AI, notably:

  • Explainable Artificial Intelligence (XAI)
  • Adversarial Robustness in Machine Learning
  • Machine Learning and Data Classification
  • Anomaly Detection Techniques and Applications
  • Advanced Neural Network Applications
  • Privacy-Preserving Technologies in Data
  • Domain Adaptation and Few-Shot Learning

Wojciech Samek has published extensively, including highly cited papers such as:

  • Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications, 2021, Proceedings of the IEEE
  • Artificial Intelligence in Dentistry: Chances and Challenges, 2020, Journal of Dental Research
  • PTB-XL, a large publicly available electrocardiography dataset, 2020, Scientific Data
  • Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions, 2024, Information Fusion
  • Pruning by explaining: A novel criterion for deep neural network pruning, 2021, Pattern Recognition

Frequent collaborators include Sebastian Lapuschkin, Klaus-Robert Müller, Thomas Wiegand, Frederik Pahde, and Grégoire Montavon. This network of coauthors indicates active engagement in collaborative research efforts centered around explainable AI and machine learning methods.

Wojciech Samek's work is frequently published in venues such as:

  • arXiv (Cornell University)
  • Information Fusion
  • Zenodo (CERN European Organization for Nuclear Research)
  • Journal of Dental Research
  • Pattern Recognition

In addition to journal papers, the scientist has contributed to academic literature through books, including a publication with Cambridge University Press titled Mathematical Aspects of Deep Learning (2022).

Best Publications

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

    Sebastian Bach;Alexander Binder;Grégoire Montavon;Frederick Klauschen

  • Methods for interpreting and understanding deep neural networks

    Grégoire Montavon;Wojciech Samek;Klaus Robert Müller;Klaus Robert Müller;Klaus Robert Müller

  • Explaining nonlinear classification decisions with deep Taylor decomposition

    Grégoire Montavon;Sebastian Lapuschkin;Alexander Binder;Wojciech Samek

  • A Unifying Review of Deep and Shallow Anomaly Detection

    Lukas Ruff;Jacob R. Kauffmann;Robert A. Vandermeulen;Gregoire Montavon

  • Unmasking Clever Hans predictors and assessing what machines really learn.

    Sebastian Lapuschkin;Stephan Wäldchen;Alexander Binder;Grégoire Montavon

  • Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models

    Wojciech Samek;Thomas Wiegand;Klaus-Robert Müller

  • Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data

    Felix Sattler;Simon Wiedemann;Klaus-Robert Muller;Wojciech Samek

  • Evaluating the Visualization of What a Deep Neural Network Has Learned

    Wojciech Samek;Alexander Binder;Gregoire Montavon;Sebastian Lapuschkin

  • Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment

    Sebastian Bosse;Dominique Maniry;Klaus-Robert Muller;Thomas Wiegand

  • Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

    Wojciech Samek;Gregoire Montavon;Sebastian Lapuschkin;Christopher J. Anders

  • Explainable ai – preface

    Wojciech Samek;Grégoire Montavon;Andrea Vedaldi;Lars Kai Hansen

  • Artificial Intelligence in Dentistry: Chances and Challenges.

    F. Schwendicke;W. Samek;J. Krois

  • PTB-XL, a large publicly available electrocardiography dataset

    Patrick Wagner;Patrick Wagner;Patrick Wagner;Nils Strodthoff;Ralf-Dieter Bousseljot;Dieter Kreiseler

  • Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints

    Felix Sattler;Klaus-Robert Muller;Wojciech Samek

  • Layer-Wise Relevance Propagation: An Overview

    Grégoire Montavon;Alexander Binder;Sebastian Lapuschkin;Wojciech Samek

  • Towards Explainable Artificial Intelligence

    Wojciech Samek;Klaus Robert Müller;Klaus Robert Müller;Klaus Robert Müller

  • Explainable AI Methods - A Brief Overview

    Unknown

  • Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers

    Alexander Binder;Grégoire Montavon;Sebastian Lapuschkin;Klaus-Robert Müller;Klaus-Robert Müller

  • Interpretable deep neural networks for single-trial EEG classification

    Irene Sturm;Sebastian Lapuschkin;Wojciech Samek;Klaus Robert Müller

  • Explaining Recurrent Neural Network Predictions in Sentiment Analysis

    Leila Arras;Grégoire Montavon;Klaus-Robert Müller;Wojciech Samek

  • Robust and Communication-Efficient Federated Learning from Non-IID Data

    Felix Sattler;Simon Wiedemann;Klaus-Robert Müller;Wojciech Samek

  • Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers

    Alexander Binder;Grégoire Montavon;Sebastian Bach;Klaus-Robert Müller

Frequent Co-Authors

Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Grégoire Montavon
Grégoire Montavon Freie Universität Berlin
Thomas Wiegand
Thomas Wiegand Technical University of Berlin
Detlev Marpe
Detlev Marpe Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
Heiko Schwarz
Heiko Schwarz Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
Hauke R. Heekeren
Hauke R. Heekeren Universität Hamburg
Gitta Kutyniok
Gitta Kutyniok Ludwig-Maximilians-Universität München
Thomas Schierl
Thomas Schierl Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
Peter Eisert
Peter Eisert Humboldt-Universität zu Berlin
Guido Nolte
Guido Nolte Universität Hamburg

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