Clemens Elster

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 26

Top Topics

Bayesian Inference

Top Venues

Mach. Learn. Sci. Technol.

SIAM J. Imaging Sci.

Publications

Manuel Marschall, Gerd Wübbeler, Franko Schmähling, Clemens Elster
Generative models and Bayesian inversion using Laplace approximation. Comput. Stat. 39 (3) (2024)
Narbota Amanova, Jörg Martin, Clemens Elster
Finding the input features that reduce the entropy of a neural network's prediction. Appl. Intell. 54 (2) (2024)
Franko Schmähling, Jörg Martin, Clemens Elster
A framework for benchmarking uncertainty in deep regression. Appl. Intell. 53 (8) (2023)
Jörg Martin, Clemens Elster
Aleatoric Uncertainty for Errors-in-Variables Models in Deep Regression. Neural Process. Lett. 55 (4) (2023)
Josua Faller, Narbota Amanova, Ruben E. van Engen, Jörg Martin, Clemens Elster
About the generalizability of deep learning based image quality assessment in mammography. Mach. Learn. Sci. Technol. 4 (4) (2023)
Manuel Marschall, Gerd Wübbeler, Franko Schmähling, Clemens Elster
Generative models and Bayesian inversion using Laplace approximation. CoRR (2022)
Selma Metzner, Bernd Kästner, Manuel Marschall, Gerd Wübbeler, Stefan Wundrack, Andrey Bakin, Arne Hoehl, Eckart Rühl, Clemens Elster
Assessment of sub-sampling schemes for compressive nano-FTIR imaging. CoRR (2022)
Narbota Amanova, Jörg Martin, Clemens Elster
Explainability for deep learning in mammography image quality assessment. Mach. Learn. Sci. Technol. 3 (2) (2022)
Selma Metzner, Bernd Kästner, Manuel Marschall, Gerd Wübbeler, Stefan Wundrack, Andrey Bakin, Arne Hoehl, Eckart Rühl, Clemens Elster
Assessment of Subsampling Schemes for Compressive Nano-FTIR Imaging. IEEE Trans. Instrum. Meas. 71 (2022)
Lara Hoffmann, Clemens Elster
Deep Ensembles from a Bayesian Perspective. CoRR (2021)
Lara Hoffmann, Ines Fortmeier, Clemens Elster
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements. CoRR (2021)
Lara Hoffmann, Ines Fortmeier, Clemens Elster
Uncertainty quantification by ensemble learning for computational optical form measurements. Mach. Learn. Sci. Technol. 2 (3) (2021)
Jörg Martin, Clemens Elster
Errors-in-Variables for deep learning: rethinking aleatoric uncertainty. CoRR (2021)
Franko Schmähling, Jörg Martin, Clemens Elster
A framework for benchmarking uncertainty in deep regression. CoRR (2021)
Jörg Martin, Clemens Elster
Detecting unusual input to neural networks. Appl. Intell. 51 (4) (2021)
Lara Hoffmann, Clemens Elster
Deep Neural Networks for Computational Optical Form Measurements. CoRR (2020)
Jörg Martin, Clemens Elster
Inspecting adversarial examples using the fisher information. Neurocomputing 382 (2020)
Tobias Kretz, Klaus-Robert Müller, Tobias Schaeffter, Clemens Elster
Mammography Image Quality Assurance Using Deep Learning. IEEE Trans. Biomed. Eng. 67 (12) (2020)
Jörg Martin, Clemens Elster
Detecting unusual input to neural networks. CoRR (2020)
Judith Lehnert, Christoph Kolbitsch, Gerd Wübbeler, Amedeo Chiribiri, Tobias Schaeffter, Clemens Elster
Large-Scale Bayesian Spatial-Temporal Regression with Application to Cardiac MR-Perfusion Imaging. SIAM J. Imaging Sci. 12 (4) (2019)
Jörg Martin, Clemens Elster
Inspecting adversarial examples using the Fisher information. CoRR (2019)
Katy Klauenberg, Rainer Kramer, Corinna Kroner, Jürgen Rose, Clemens Elster
Reducing sample size by tightening test conditions. Qual. Reliab. Eng. Int. 34 (3) (2018)
Alexander Khanin, Mathias Anton, Marcel Reginatto, Clemens Elster
Assessment of CT Image Quality Using a Bayesian Framework. IEEE Trans. Medical Imaging 37 (12) (2018)
Gerd Wübbeler, Clemens Elster
A Large-Scale Optimization Method Using a Sparse Approximation of the Hessian for Magnetic Resonance Fingerprinting. SIAM J. Imaging Sci. 10 (3) (2017)
Clemens Elster, Gerd Wübbeler
Bayesian inference using a noninformative prior for linear Gaussian random coefficient regression with inhomogeneous within-class variances. Comput. Stat. 32 (1) (2017)
Sascha Eichstädt, Natallia Makarava, Clemens Elster
On the evaluation of uncertainties for state estimation with the Kalman filter. CoRR (2016)
Ignacio Lira, Anna Chunovkina, Clemens Elster, Wolfgang Woger
Analysis of Key Comparisons Incorporating Knowledge About Bias. IEEE Trans. Instrum. Meas. 61 (8) (2012)
Clemens Elster, Ignacio Lira
On the choice of a noninformative prior for Bayesian inference of discretized normal observations. Comput. Stat. 27 (2) (2012)
Florian Kohl, Gerd Wübbeler, Dorothea Kolossa, Clemens Elster, Markus Bär, Reinhold Orglmeister
Noise Adjusted PCA for Finding the Subspace of Evoked Dependent Signals from MEG Data. LVA/ICA (2010)
Sascha Eichstädt, Alfred Link, Clemens Elster
Dynamic Uncertainty for Compensated Second-Order Systems. Sensors 10 (8) (2010)
Gerd Wübbeler, Clemens Elster, Thomas M. Reichel, Rolf Judaschke
Determination of the Complex Residual Error Parameters of a Calibrated One-Port Vector Network Analyzer. IEEE Trans. Instrum. Meas. 58 (9) (2009)
Florian Kohl, Gerd Wübbeler, Dorothea Kolossa, Clemens Elster, Markus Bär, Reinhold Orglmeister
Non-independent BSS: A Model for Evoked MEG Signals with Controllable Dependencies. ICA (2009)
Gerd Wübbeler, Manuel Stavridis, Dieter Kreiseler, Ralf-Dieter Bousseljot, Clemens Elster
Verification of humans using the electrocardiogram. Pattern Recognit. Lett. 28 (10) (2007)
R. Arnold Nicolaus, Clemens Elster
Diameter determination of Avogadro Spheres #1 and #2. IEEE Trans. Instrum. Meas. 54 (2) (2005)
A. Salajegheh, Alfred Link, Clemens Elster, Martin Burghoff, Tilmann Heinrich Sander, Lutz Trahms, David Poeppel
Systematic latency variation of the auditory evoked M100: from average to single-trial data. NeuroImage 23 (1) (2004)
Clemens Elster, Arnold Neumaier
A Method of Trust Region Type for Minimizing Noisy Functions. Computing 58 (1) (1997)