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2020 – today
- 2023
[j52]Leander Weber
, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond explaining: Opportunities and challenges of XAI-based model improvement. Inf. Fusion 92: 154-176 (2023)- [j51]Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li:
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. IEEE Internet Things J. 10(4): 3642-3663 (2023) - [j50]Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni, Simon Colreavy-Donnelly, Wojciech Samek, Miguel A. Molina-Cabello, Ezequiel López-Rubio:
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. IEEE Trans. Artif. Intell. 4(2): 282-291 (2023) - [j49]Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jérôme Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti:
Data Models for Dataset Drift Controls in Machine Learning With Optical Images. Trans. Mach. Learn. Res. 2023 (2023) - [i100]Anna Hedström, Philine Bommer, Kristoffer K. Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne:
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. CoRR abs/2302.07265 (2023) - [i99]David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek:
A Privacy Preserving System for Movie Recommendations using Federated Learning. CoRR abs/2303.04689 (2023) - [i98]Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek:
Explainable AI for Time Series via Virtual Inspection Layers. CoRR abs/2303.06365 (2023) - [i97]Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin:
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. CoRR abs/2303.12641 (2023) - [i96]Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin, Wojciech Samek, Johanna Vielhaben:
XAI-based Comparison of Input Representations for Audio Event Classification. CoRR abs/2304.14019 (2023) - 2022
- [j48]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) - [j47]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) - [j46]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) - [j45]Andreas Holzinger, Matthias Dehmer, Frank Emmert-Streib, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurisica, Natalia Díaz Rodríguez:
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence. Inf. Fusion 79: 263-278 (2022) - [j44]Leila Arras, Ahmed Osman, Wojciech Samek:
CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations. Inf. Fusion 81: 14-40 (2022) - [j43]Simon M. Hofmann, Frauke Beyer, Sebastian Lapuschkin, Ole Goltermann, Markus Loeffler, Klaus-Robert Müller, Arno Villringer, Wojciech Samek, Anja Veronica Witte:
Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. NeuroImage 261: 119504 (2022) - [j42]Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. IEEE Signal Process. Mag. 39(4): 40-58 (2022) - [j41]Heiner Kirchhoffer, Paul Haase, Wojciech Samek, Karsten Müller, Hamed Rezazadegan Tavakoli, Francesco Cricri, Emre B. Aksu, Miska M. Hannuksela, Wei Jiang, Wei Wang, Shan Liu, Swayambhoo Jain, Shahab Hamidi-Rad, Fabien Racapé, Werner Bailer:
Overview of the Neural Network Compression and Representation (NNR) Standard. IEEE Trans. Circuits Syst. Video Technol. 32(5): 3203-3216 (2022) - [j40]Felix Sattler, Arturo Marbán, Roman Rischke, Wojciech Samek:
CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding. IEEE Trans. Netw. Sci. Eng. 9(4): 2025-2038 (2022) - [c68]K.-R. Müller, A. W. Thomas, Wojciech Samek:
Deep Learning for Whole-Brain Cognitive Decoding. BCI 2022: 1-3 - [c67]Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin:
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI. CD-MAKE 2022: 1-18 - [c66]Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek:
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. CVPR Workshops 2022: 3366-3375 - [c65]Gerhard Tech, Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Jonathan Pfaff, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
History Dependent Significance Coding for Incremental Neural Network Compression. ICIP 2022: 3541-3545 - [c64]Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek:
FedAUXfdp: Differentially Private One-Shot Federated Distillation. FL@IJCAI 2022: 100-114 - [e2]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. Lecture Notes in Computer Science 13200, Springer 2022, ISBN 978-3-031-04082-5 [contents] - [i95]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) - [i94]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) - [i93]Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek:
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement. CoRR abs/2203.08008 (2022) - [i92]Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek:
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. CoRR abs/2204.04424 (2022) - [i91]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) - [i90]Leon Witt, Mathis Heyer, Kentaroh Toyoda, Wojciech Samek, Dan Li:
Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review. CoRR abs/2205.07855 (2022) - [i89]Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek:
FedAUXfdp: Differentially Private One-Shot Federated Distillation. CoRR abs/2205.14960 (2022) - [i88]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) - [i87]Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jérôme Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti:
Data Models for Dataset Drift Controls in Machine Learning With Images. CoRR abs/2211.02578 (2022) - [i86]Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. CoRR abs/2211.11426 (2022) - [i85]Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek:
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CoRR abs/2211.12486 (2022) - [i84]Fabian Horst, Djordje Slijepcevic, Matthias Zeppelzauer, Anna-Maria Raberger, Sebastian Lapuschkin, Wojciech Samek, Wolfgang Immanuel Schöllhorn, Christian Breiteneder, Brian Horsak:
Explaining automated gender classification of human gait. CoRR abs/2211.17015 (2022) - [i83]Djordje Slijepcevic, Fabian Horst, Marvin Simak, Sebastian Lapuschkin, Anna-Maria Raberger, Wojciech Samek, Christian Breiteneder, Wolfgang Immanuel Schöllhorn, Matthias Zeppelzauer, Brian Horsak:
Explaining machine learning models for age classification in human gait analysis. CoRR abs/2211.17016 (2022) - [i82]Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin:
Optimizing Explanations by Network Canonization and Hyperparameter Search. CoRR abs/2211.17174 (2022) - 2021
- [j39]Luis Oala, Cosmas Heiß, Jan MacDonald, Maximilian März, Gitta Kutyniok, Wojciech Samek:
Detecting failure modes in image reconstructions with interval neural network uncertainty. Int. J. Comput. Assist. Radiol. Surg. 16(12): 2089-2097 (2021) - [j38]Luis Oala, Andrew G. Murchison, Pradeep Balachandran, Shruti Choudhary, Jana Fehr, Alixandro Werneck Leite, Peter G. Goldschmidt, Christian Johner, Elora D. M. Schörverth, Rose Nakasi, Martin Meyer, Federico Cabitza, Pat Baird, Carolin Prabhu, Eva Weicken, Xiaoxuan Liu, Markus Wenzel, Steffen Vogler, Darlington Ahiale Akogo, Shada Alsalamah, Emre Kazim, Adriano S. Koshiyama, Sven Piechottka, Sheena Macpherson, Ian Shadforth, Regina Geierhofer, Christian Matek, Joachim Krois, Bruno Sanguinetti, Matthew Arentz, Pavol Bielik, Saúl Calderón Ramírez, Auss Abbood, Nicolas Langer, Stefan Haufe, Ferath Kherif, Sameer Pujari, Wojciech Samek, Thomas Wiegand:
Machine Learning for Health: Algorithm Auditing & Quality Control. J. Medical Syst. 45(12): 105 (2021) - [j37]Vignesh Srinivasan, Csaba Rohrer, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Robustifying models against adversarial attacks by Langevin dynamics. Neural Networks 137: 1-17 (2021) - [j36]Simon Wiedemann, Suhas Shivapakash, Daniel Becking, Pablo Wiedemann, Wojciech Samek, Friedel Gerfers, Thomas Wiegand:
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4Bit-Compact Multilayer Perceptrons. IEEE Open J. Circuits Syst. 2: 407-419 (2021) - [j35]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) - [j34]Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller:
A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE 109(5): 756-795 (2021) - [j33]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) - [j32]Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek:
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. IEEE J. Biomed. Health Informatics 25(5): 1519-1528 (2021) - [j31]Felix Sattler, Klaus-Robert Müller, Wojciech Samek:
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints. IEEE Trans. Neural Networks Learn. Syst. 32(8): 3710-3722 (2021) - [c63]Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek:
Interval Neural Networks as Instability Detectors for Image Reconstructions. Bildverarbeitung für die Medizin 2021: 324-329 - [c62]Paul Haase, Daniel Becking, Heiner Kirchhoffer, Karsten Müller, Heiko Schwarz, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
Encoder Optimizations For The NNR Standard On Neural Network Compression. ICIP 2021: 3522-3526 - [i81]Felix Sattler, Tim Korjakow, Roman Rischke, Wojciech Samek:
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning. CoRR abs/2102.02514 (2021) - [i80]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) - [i79]Vignesh Srinivasan, Nils Strodthoff, Jackie Ma, Alexander Binder, Klaus-Robert Müller, Wojciech Samek:
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. CoRR abs/2106.13497 (2021) - [i78]Leon Witt, Usama Zafar, KuoYeh Shen, Felix Sattler, Dan Li, Wojciech Samek:
Reward-Based 1-bit Compressed Federated Distillation on Blockchain. CoRR abs/2106.14265 (2021) - [i77]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) - [i76]Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller:
Evaluating deep transfer learning for whole-brain cognitive decoding. CoRR abs/2111.01562 (2021) - [i75]Simon Letzgus, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Toward Explainable AI for Regression Models. CoRR abs/2112.11407 (2021) - 2020
- [j30]Nils Strodthoff, Patrick Wagner, Markus Wenzel, Wojciech Samek:
UDSMProt: universal deep sequence models for protein classification. Bioinform. 36(8): 2401-2409 (2020) - [j29]Johanna Vielhaben, Markus Wenzel, Wojciech Samek, Nils Strodthoff:
USMPep: universal sequence models for major histocompatibility complex binding affinity prediction. BMC Bioinform. 21(1): 279 (2020) - [j28]Clemens Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert:
Accurate and robust neural networks for face morphing attack detection. J. Inf. Secur. Appl. 53: 102526 (2020) - [j27]Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Tung Nguyen, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek:
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. IEEE J. Sel. Top. Signal Process. 14(4): 700-714 (2020) - [j26]Wojciech Samek:
Learning with explainable trees. Nat. Mach. Intell. 2(1): 16-17 (2020) - [j25]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand:
Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements. npj Digit. Medicine 3 (2020) - [j24]Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Compact and Computationally Efficient Representation of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 31(3): 772-785 (2020) - [j23]Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek:
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3400-3413 (2020) - [c61]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI 2020: 5842-5850 - [c60]Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek:
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CVPR Workshops 2020: 3096-3104 - [c59]Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek:
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CVPR Workshops 2020: 3105-3113 - [c58]Felix Sattler, Klaus-Robert Müller, Thomas Wiegand, Wojciech Samek:
On the Byzantine Robustness of Clustered Federated Learning. ICASSP 2020: 8861-8865 - [c57]David Neumann, Felix Sattler, Heiner Kirchhoffer, Simon Wiedemann, Karsten Müller, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek:
Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates. ICIP 2020: 21-25 - [c56]Paul Haase, Heiko Schwarz, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Arturo Marbán, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand:
Dependent Scalar Quantization For Neural Network Compression. ICIP 2020: 36-40 - [c55]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML 2020: 3-10 - [c54]Andreas Holzinger, Anna Saranti, Christoph Molnar, Przemyslaw Biecek, Wojciech Samek:
Explainable AI Methods - A Brief Overview. xxAI@ICML 2020: 13-38 - [c53]Grégoire Montavon, Jacob R. Kauffmann, Wojciech Samek, Klaus-Robert Müller:
Explaining the Predictions of Unsupervised Learning Models. xxAI@ICML 2020: 117-138 - [c52]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 - [c51]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 - [c50]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 - [c49]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 - [i74]Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder:
Understanding Image Captioning Models beyond Visualizing Attention. CoRR abs/2001.01037 (2020) - [i73]Felix Sattler, Thomas Wiegand, Wojciech Samek:
Trends and Advancements in Deep Neural Network Communication. CoRR abs/2003.03320 (2020) - [i72]Ahmed Osman, Leila Arras, Wojciech Samek:
Towards Ground Truth Evaluation of Visual Explanations. CoRR abs/2003.07258 (2020) - [i71]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) - [i70]Luis Oala, Cosmas Heiss, Jan MacDonald, Maximilian März, Wojciech Samek, Gitta Kutyniok:
Interval Neural Networks: Uncertainty Scores. CoRR abs/2003.11566 (2020) - [i69]Jan MacDonald, Maximilian März, Luis Oala, Wojciech Samek:
Interval Neural Networks as Instability Detectors for Image Reconstructions. CoRR abs/2003.13471 (2020) - [i68]Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek:
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CoRR abs/2004.01077 (2020) - [i67]Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek:
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CoRR abs/2004.04729 (2020) - [i66]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) - [i65]Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand:
Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements. CoRR abs/2004.11841 (2020) - [i64]Nils Strodthoff, Patrick Wagner, Tobias Schaeffter, Wojciech Samek:
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. CoRR abs/2004.13701 (2020) - [i63]Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello:
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures. CoRR abs/2006.07767 (2020) - [i62]Anko Börner, Heinz-Wilhelm Hübers, Odej Kao, Florian Schmidt, Soeren Becker, Joachim Denzler, Daniel Matolin, David Haber, Sergio Lucia, Wojciech Samek, Rudolph Triebel, Sascha Eichstädt, Felix Bießmann, Anna M. Kruspe, Peter Jung, Manon Kok, Guillermo Gallego, Ralf Berger:
Sensor Artificial Intelligence and its Application to Space Systems - A White Paper. CoRR abs/2006.08368 (2020) - [i61]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) - [i60]Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Langevin Cooling for Domain Translation. CoRR abs/2008.13723 (2020) - [i59]Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller:
A Unifying Review of Deep and Shallow Anomaly Detection. CoRR abs/2009.11732 (2020) - [i58]Felix Sattler, Arturo Marbán, Roman Rischke, Wojciech Samek:
Communication-Efficient Federated Distillation. CoRR abs/2012.00632 (2020) - [i57]Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann, Daniel Becking, Wojciech Samek, Friedel Gerfers, Thomas Wiegand:
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons. CoRR abs/2012.11331 (2020)
2010 – 2019
- 2019
- [j22]Arturo Marbán, Vignesh Srinivasan, Wojciech Samek, Josep Fernández, Alicia Casals:
A recurrent convolutional neural network approach for sensorless force estimation in robotic surgery. Biomed. Signal Process. Control. 50: 134-150 (2019) - [j21]Ahmed Osman, Wojciech Samek:
DRAU: Dual Recurrent Attention Units for Visual Question Answering. Comput. Vis. Image Underst. 185: 24-30 (2019) - [j20]Guangtao Zhai, Ke Gu, Jiheng Wang, Wojciech Samek:
Quality perception of advanced multimedia systems. Digit. Signal Process. 91: 1-2 (2019) - [j19]Sebastian Bosse, Sören Becker, Klaus-Robert Müller, Wojciech Samek, Thomas Wiegand:
Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network. Digit. Signal Process. 91: 54-65 (2019) - [j18]Sergio Cruces, Rubén Martín-Clemente, Wojciech Samek:
Information Theory Applications in Signal Processing. Entropy 21(7): 653 (2019) - [j17]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) - [j16]Nils Strodthoff, Baris Göktepe, Thomas Schierl, Cornelius Hellge, Wojciech Samek:
Enhanced Machine Learning Techniques for Early HARQ Feedback Prediction in 5G. IEEE J. Sel. Areas Commun. 37(11): 2573-2587 (2019) - [c48]Johanna Vielhaben, Hüseyin Camalan, Wojciech Samek, Markus Wenzel:
Viewport Forecasting in 360° Virtual Reality Videos with Machine Learning. AIVR 2019: 74-81 - [c47]Leila Arras, Ahmed Osman, Klaus-Robert Müller, Wojciech Samek:
Evaluating Recurrent Neural Network Explanations. BlackboxNLP@ACL 2019: 113-126 - [c46]Jan Laermann, Wojciech Samek, Nils Strodthoff:
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training. GCPR 2019: 360-373 - [c45]Patrick Wagner, Jakob Paul Morath, Arturo Zychlinsky, Klaus-Robert Müller, Wojciech Samek:
Rotation Invariant Clustering of 3D Cell Nuclei Shapes. EMBC 2019: 6022-6027 - [c44]Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima:
Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. EUSIPCO 2019: 1-5 - [c43]Talmaj Marinc, Vignesh Srinivasan, Serhan Gül, Cornelius Hellge, Wojciech Samek:
Multi-Kernel Prediction Networks for Denoising of Burst Images. ICIP 2019: 2404-2408 - [c42]