Publications

250 entries « 1 of 5 »

2020

Ghanbari, M; Ohler, U

Deep neural networks for interpreting RNA-binding protein target preferences Journal Article

Genome Research, 2020 Jan 28 , 2020.

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2019

Lalli, R; Howey, R; Wintergrün, D

The dynamics of collaboration networks and the history of general relativity, 1925–1970 Journal Article

Scientometrics , 2019.

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Valleriani, M; Kräutli, F; Zamani, M; Tejedor, A; Sander, C; Vogl, M; Bertram, S; Funke, G; Kantz, H

The Emergence of Epistemic Communities in the Sphaera Corpus Journal Article

Journal of Historical Network Research, 3 (1), pp. 50-91, 2019.

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Vidaurre, C; Nolte, G; de Vries, IEJ; Gómez, M; Boonstra, TW; Müller, KR; Villringer, A; Nikulin, VV

Canonical maximization of coherence: A novel tool for investigation of neuronal interactions between two datasets Journal Article

NeuroImage, 201 , 2019.

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von Lühmann, A; Boukouvalas, Z; Müller, KR; Adalı, T

A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy Journal Article

NeuroImage, 200 , pp. 72-88, 2019.

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Vidaurre, C; Murguialday, AR; Haufe, S; Gómez, M; Müller, KR; Nikulin, VV

Enhancing sensorimotor BCI performance with assistive afferent activity: An online evaluation Journal Article

NeuroImage, 199 , pp. 375-386, 2019.

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Sauceda, HE; Chmiela, S; Poltavsky, I; Müller, KR; Tkatchenko, A

Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights Journal Article

2019.

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Schütt, KT; Gastegger, M; Tkatchenko, A; Müller, KR

Quantum-Chemical Insights from Interpretable Atomistic Neural Networks Book Chapter

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, pp. 311-330, Springer International Publishing, 2019, ISBN: 978-3-030-28953-9.

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Samek, W; Müller, KR

Towards Explainable Artificial Intelligence Book Chapter

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, pp. 5-22, Springer International Publishing, 2019, ISBN: 978-3-030-28954-6.

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Laubichler, MD; Maienschein, J; Renn, J

Computational History of Knowledge: Challenges and Opportunities Journal Article

Isis, 110 (3), pp. 502–512, 2019.

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Iravani, S; Conrad, TOF

Deep Learning for Proteomics Data for Feature Selection and Classification Inproceedings

Machine Learning and Knowledge Extraction, pp. 301-316, Springer International Publishing, 2019, ISBN: 978-3-030-29726-8.

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Hägele, M; Seegerer, P; Lapuschkin, S; Bockmayr, M; Samek, W; Klauschen, F; Müller, KR; Binder, A

Resolving challenges in deep learning-basedanalyses of histopathological images usingexplanation methods Journal Article

https://arxiv.org/abs/1908.06943, 2019.

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Alber, M; Lapuschkin, S; Seegerer, P; Hägele, M; Schütt, KT; Montavon, G; Samek, W; Müller, KR; Dähne, S; Kindermans, PJ

iNNvestigate neural networks! Journal Article

2019.

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Bosse, S; Becker, S; Müller, KR; Samek, W; Wiegand, T

Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network Journal Article

Digital Signal Processing, 91 , pp. 54-65, 2019.

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Chmiela, S; Sauceda, HE; Poltavsky, I; Müller, KR; Tkatchenko, A

sGDML: Constructing accurate and data efficient molecular force fields using machine learning Journal Article

Computer Physics Communications, 240 , pp. 38-45, 2019, ISSN: 0010-4655.

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Wagner, P; Morath, JP; Zychlinsky, A; Müller, KR; Samek, W

Rotation Invariant Clustering of 3D Cell Nuclei Shapes* Proceeding

2019, (41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)).

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Schütt, KT; Gastegger, M; Tkatchenko, A; Müller, KR; Maurer, RJ

Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Journal Article

2019.

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Kauffmann, J; Esders, M; Montavon, G; Samek, W; Müller, KR

From Clustering to Cluster Explanations via Neural Networks Journal Article

2019.

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Ruff, L; Vandermeulen, RA; Görnitz, N; Binder, A; Müller, E; Müller, KR; Kloft, M

Deep Semi-Supervised Anomaly Detection Journal Article

2019.

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Gebauer, NWA; Gastegger, M; Schütt, KT

Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Journal Article

2019.

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Wiedemann, S; Müller, KR; Samek, W

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Journal Article

IEEE Transactions on Neural Networks and Learning Systems, 2019.

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Wiedemann, S; Müller, KR; Samek, W

Compact and Computationally Efficient Representation of Deep Neural Networks Journal Article

IEEE Transactions on Neural Networks and Learning Systems, pp. 1-14, 2019.

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Bogojeski, M; Vogt-Maranto, L; Tuckerman, ME; Müller, KR; Burke, K

Density Functionals with Quantum Chemical Accuracy: From Machine Learning to Molecular Dynamics Journal Article Forthcoming

Forthcoming.

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Zhou, JT; Tsang, IW; KR, SS Ho; Müller,

N-ary decomposition for multi-class classification Journal Article

Machine Learning, 108 (5), pp. 809-830, 2019.

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Arras, L; Osman, A; Müller, KR; Samek, W

Evaluating Recurrent Neural Network Explanations Journal Article

2019.

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Bauer, A; Nakajima, S; Goernitz, N; Müller, KR

Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs Inproceedings

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019 , pp. 1696–1703, 2019.

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Schwenk, G; Pabst, R; Müller, KR

Classification of structured validation data using stateless and stateful features Journal Article

Computer Communications, 138 , pp. 54-66, 2019.

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Srinivasan, V; Kuruoglu, EE; Müller, KR; Samek, W; Nakajima, S

Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution Journal Article

2019.

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Redyuk, S

Automated Documentation of End-to-End Experiments in Data Science Inproceedings

2019 IEEE 35th International Conference on Data Engineering (ICDE), pp. 2076-2080, 2019.

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Nicoli, K; Kessel, P; Strodthoff, N; Samek, W; Müller, KR; Nakajima, S

Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling Journal Article

2019.

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Lapuschkin, S; Wäldchen, S; Binder, A; Montavon, G; Müller, Samek & KR W

Unmasking Clever Hans predictors and assessing what machines really learn Journal Article

Nature Communications, 10 (1096), 2019.

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Sattler, F; Wiedemann, S; Müller, KR; Samek, W

Robust and Communication-Efficient Federated Learning from Non-IID Data Journal Article

2019.

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Helmers, L; Horn, F; Biegler, F; Oppermann, T; Müller, KR

Automating the search for a patent’s prior art with a full text similarity search Journal Article

PLoS ONE, 14 (3), pp. 1-17, 2019.

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Horst, F; Lapuschkin, S; Samek, W; Müller, KR; Schöllhorn, WI

Explaining the unique nature of individual gait patterns with deep learning Journal Article

Scientific Reports, 9 (1), pp. 2391, 2019.

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Müller, KR

Explainable Deep Learning for Analysing Brain Data Inproceedings

2019 7th International Winter Conference on Brain-Computer Interface (BCI) , 2019.

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Montavon, G

Gradient-Based Vs. Propagation-Based Explanations: An Axiomatic Comparison Book Chapter

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning , pp. 253-265, Springer International Publishing, 2019, ISBN: 978-3-030-28954-6.

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Montavon, G; Binder, A; Lapuschkin, S; Samek, W; Müller, KR

Layer-Wise Relevance Propagation: An Overview Book Chapter

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning , pp. 193-209, Springer International Publishing, 2019, ISBN: 978-3-030-28954-6.

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Jurmeister, P; Bockmayr, M; Seegerer, P; Bockmayr, T; Treue, D; Montavon, G; Vollbrecht, C; Arnold, A; Teichmann, D; Bressem, K; Schüller, U; von Laffert, M; Müller, KR; Capper, D; Klauschen, F

Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases Journal Article

Science Translational Medicine, 2019.

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Sauceda, HE; Chmiela, S; Poltavsky, I; Müller, KR; Tkatchenko, A

Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces Journal Article

The Journal of Chemical Physics, 150 (11), 2019.

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Anders, CJ; Montavon, G; Samek, W; Müller, KR

Understanding Patch-Based Learning of Video Data by Explaining Predictions Book Chapter

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning , pp. 297-309, Springer International Publishing, 2019, ISBN: 978-3-030-28954-6.

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Srinivasan, V; Marban, A; Müller, KR; Samek, W; Nakajima, S

Defense Against Adversarial Attacks by Langevin Dynamics Proceeding

2019, (ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning).

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2018

Wiedemann, S; Marban, A; Müller, KR; Samek, W

Entropy-Constrained Training of Deep Neural Networks Journal Article

2018.

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Breβ, S; Köcher, B; Funke, H; Zeuch, S; Rabl, T; Markl, V

Generating custom code for efficient query execution on heterogeneous processors Journal Article

The International Journal on Very Large Data Bases, 27 (6), pp. 797-822, 2018.

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Klus, S; Bittracher, A; Schuster, I; Schütte, C

A kernel-based approach to molecular conformation analysis Journal Article

Journal of Chemical Physics, 149 (24), 2018.

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Gebauer, NWA; Gastegger, M; Schütt, KT

Generating equilibrium molecules with deep neural networks Journal Article

2018.

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Nicoli, KA; and M and KT Schütt, Kessel Gastegger P

Analysis of Atomistic Representations Using Weighted Skip-Connections Proceeding

2018, (NIPS 2018 Workshop: Machine Learning for Molecules and Materials).

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Kaltenstadler, S; Nakajima, Shinichi; and W Samek, KR Müller

Wasserstein Stationary Subspace Analysis Journal Article

IEEE Journal of Selected Topics in Signal Processing, 12 (6), pp. 1213-1223, 2018.

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Meyer, A; Zverinski, D; Pfahringer, B; Kempfert, J; Kuehne, T; Sündermann, S; Stamm, C; Hofmann, T; Falk, V; Eickhoff, C

Machine learning for real-time prediction of complications in critical care: a retrospective study Journal Article

The Lancet Respiratory Medicine, 6 , 2018.

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Sattler, F; Wiedemann, S; Müller, KR; Samek, W

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication Journal Article

2018.

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Reisenhofer, R; Bosse, S; Kutyniok, G; Wiegand, T

A Haar wavelet-based perceptual similarity index for image quality assessment Journal Article

Signal Processing: Image Communication, 61 , pp. 31-33, 2018.

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250 entries « 1 of 5 »