Samek, Wojciech

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

Bach, S., Binder, A., Montavon, G., Klauschen, F., Müller, K.-R., & Samek, W. (2015) · PLOS ONE

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 4,524

Methods for interpreting and understanding deep neural networks

Montavon, G., Samek, W., & Müller, K.-R. (2018) · Digital Signal Processing

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 2,665

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

Sattler, F., Wiedemann, S., Muller, K.-R., & Samek, W. (2020) · IEEE Transactions on Neural Networks and Learning Systems

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 1,725

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

Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Muller, K.-R. (2021) · Proceedings of the IEEE

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 1,477

Artificial Intelligence in Dentistry: Chances and Challenges

Schwendicke, F., Samek, W., & Krois, J. (2020) · Journal of Dental Research

Artificial Intelligence in Healthcare and EducationDental Radiography and Imaging

Cited by 1,446

Explaining nonlinear classification decisions with deep taylor decomposition

Montavon, G., Lapuschkin, S., Binder, A., Samek, W., & Müller, K.-R. (2017) · Pattern Recognition

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 1,357

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

Sattler, F., Muller, K.-R., & Samek, W. (2021) · IEEE Transactions on Neural Networks and Learning Systems

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 1,355

Evaluating the Visualization of What a Deep Neural Network Has Learned

Samek, W., Binder, A., Montavon, G., Lapuschkin, S., & Muller, K.-R. (2017) · IEEE Transactions on Neural Networks and Learning Systems

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 1,164

Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Samek, W., Wiegand, T., & Müller, K.-R. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 1,080

Explaining Recurrent Neural Network Predictions in Sentiment Analysis

Arras, L., Montavon, G., Müller, K.-R., & Samek, W. (2017) · Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

Explainable Artificial Intelligence (XAI)Sentiment Analysis and Opinion Mining

Cited by 361

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication

Sattler, F., Wiedemann, S., Muller, K.-R., & Samek, W. (2019) · 2019 International Joint Conference on Neural Networks (IJCNN)

Stochastic Gradient Optimization TechniquesAdvanced Neural Network Applications

Cited by 240

From attribution maps to human-understandable explanations through Concept Relevance Propagation

Achtibat, R., Dreyer, M., Eisenbraun, I., Bosse, S., Wiegand, T., Samek, W., & Lapuschkin, S. (2023) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 181

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

Hedström, A., Weber, L., Bareeva, D., Krakowczyk, D., Motzkus, F., Samek, W., Lapuschkin, S., & Höhne, M. M. C. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 116

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

Wiedemann, S., Kirchhoffer, H., Matlage, S., Haase, P., Marban, A., Marinc, T., Neumann, D., Nguyen, T., Schwarz, H., Wiegand, T., et al. (2020) · IEEE Journal of Selected Topics in Signal Processing

Advanced Data Compression TechniquesVideo Coding and Compression Technologies

Cited by 113

Explaining Machine Learning Models for Clinical Gait Analysis

Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breiteneder, C., Schöllhorn, W. I., & Zeppelzauer, M. (2022) · ACM Transactions on Computing for Healthcare

Explainable Artificial Intelligence (XAI)Gait Recognition and Analysis

Cited by 82

Machine Learning for Health: Algorithm Auditing & Quality Control

Oala, L., Murchison, A. G., Balachandran, P., Choudhary, S., Fehr, J., Leite, A. W., Goldschmidt, P. G., Johner, C., Schörverth, E. D. M., Nakasi, R., et al. (2021) · Journal of Medical Systems

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 48

Explainable AI for time series via Virtual Inspection Layers

Vielhaben, J., Lapuschkin, S., Montavon, G., & Samek, W. (2024) · Pattern Recognition

Explainable Artificial Intelligence (XAI)Time Series Analysis and Forecasting

Cited by 38

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations

Binder, A., Weber, L., Lapuschkin, S., Montavon, G., Müller, K.-R., & Samek, W. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 21

AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark

Becker, S., Vielhaben, J., Ackermann, M., Müller, K.-R., Lapuschkin, S., & Samek, W. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Music and Audio Processing

Cited by 7