Clemens Elster - researchr alias

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Viewing Publication 1 - 26 from 26

2024

Finding the input features that reduce the entropy of a neural network's predictionNarbota Amanova, Jörg Martin, Clemens Elster. apin, 54(2):1922-1936, 2024. [doi]

Generative models and Bayesian inversion using Laplace approximationManuel Marschall, Gerd Wübbeler, Franko Schmähling, Clemens Elster. cstat, 39(3):1321-1349, May 2024. [doi]

2023

About the generalizability of deep learning based image quality assessment in mammographyJosua Faller, Narbota Amanova, Ruben E. van Engen, Jörg Martin, Clemens Elster. mlst, 4(4):45001, December 2023. [doi]

Aleatoric Uncertainty for Errors-in-Variables Models in Deep RegressionJörg Martin, Clemens Elster. npl, 55(4):4799-4818, 2023. [doi]

A framework for benchmarking uncertainty in deep regressionFranko Schmähling, Jörg Martin, Clemens Elster. apin, 53(8):9499-9512, April 2023. [doi]

2022

Explainability for deep learning in mammography image quality assessmentNarbota Amanova, Jörg Martin, Clemens Elster. mlst, 3(2):25015, 2022. [doi]

Assessment of Subsampling Schemes for Compressive Nano-FTIR ImagingSelma Metzner, Bernd Kästner, Manuel Marschall, Gerd Wübbeler, Stefan Wundrack, Andrey Bakin, Arne Hoehl, Eckart Rühl, Clemens Elster. tim, 71:1-8, 2022. [doi]

2021

Uncertainty quantification by ensemble learning for computational optical form measurementsLara Hoffmann, Ines Fortmeier, Clemens Elster. mlst, 2(3):35030, September 2021. [doi]

Detecting unusual input to neural networksJörg Martin, Clemens Elster. apin, 51(4):2198-2209, 2021. [doi]

2020

Mammography Image Quality Assurance Using Deep LearningTobias Kretz, Klaus-Robert Müller, Tobias Schaeffter, Clemens Elster. tbe, 67(12):3317-3326, 2020. [doi]

Inspecting adversarial examples using the fisher informationJörg Martin, Clemens Elster. ijon, 382:80-86, 2020. [doi]

2019

Large-Scale Bayesian Spatial-Temporal Regression with Application to Cardiac MR-Perfusion ImagingJudith Lehnert, Christoph Kolbitsch, Gerd Wübbeler, Amedeo Chiribiri, Tobias Schaeffter, Clemens Elster. siamis, 12(4):2035-2062, 2019. [doi]

2018

Assessment of CT Image Quality Using a Bayesian FrameworkAlexander Khanin, Mathias Anton, Marcel Reginatto, Clemens Elster. tmi, 37(12):2687-2694, 2018. [doi]

Reducing sample size by tightening test conditionsKaty Klauenberg, Rainer Kramer, Corinna Kroner, Jürgen Rose, Clemens Elster. qre, 34(3):333-346, 2018. [doi]

2017

Bayesian inference using a noninformative prior for linear Gaussian random coefficient regression with inhomogeneous within-class variancesClemens Elster, Gerd Wübbeler. cstat, 32(1):51-69, 2017. [doi]

A Large-Scale Optimization Method Using a Sparse Approximation of the Hessian for Magnetic Resonance FingerprintingGerd Wübbeler, Clemens Elster. siamis, 10(3):979-1004, 2017. [doi]

2012

On the choice of a noninformative prior for Bayesian inference of discretized normal observationsClemens Elster, Ignacio Lira. cstat, 27(2):219-235, 2012. [doi]

Analysis of Key Comparisons Incorporating Knowledge About BiasIgnacio Lira, Anna Chunovkina, Clemens Elster, Wolfgang Woger. tim, 61(8):2079-2084, 2012. [doi]

2010

Dynamic Uncertainty for Compensated Second-Order SystemsSascha Eichstädt, Alfred Link, Clemens Elster. sensors, 10(8):7621-7631, 2010. [doi]

Noise Adjusted PCA for Finding the Subspace of Evoked Dependent Signals from MEG DataFlorian Kohl, Gerd Wübbeler, Dorothea Kolossa, Clemens Elster, Markus Bär, Reinhold Orglmeister. ica 2010: 442-449 [doi]

2009

Non-independent BSS: A Model for Evoked MEG Signals with Controllable DependenciesFlorian Kohl, Gerd Wübbeler, Dorothea Kolossa, Clemens Elster, Markus Bär, Reinhold Orglmeister. ida 2009: 443-450 [doi]

Determination of the Complex Residual Error Parameters of a Calibrated One-Port Vector Network AnalyzerGerd Wübbeler, Clemens Elster, Thomas Reichel, Rolf Judaschke. tim, 58(9):3238-3244, 2009. [doi]

2007

Verification of humans using the electrocardiogramGerd Wübbeler, Manuel Stavridis, Dieter Kreiseler, Ralf-Dieter Bousseljot, Clemens Elster. prl, 28(10):1172-1175, 2007. [doi]

2005

Diameter determination of Avogadro Spheres #1 and #2R. Arnold Nicolaus, Clemens Elster. tim, 54(2):872-876, 2005. [doi]

2004

Systematic latency variation of the auditory evoked M100: from average to single-trial dataA. Salajegheh, Alfred Link, Clemens Elster, Martin Burghoff, Tilmann Heinrich Sander, Lutz Trahms, David Poeppel. neuroimage, 23(1):288-295, 2004. [doi]

1997

A Method of Trust Region Type for Minimizing Noisy FunctionsClemens Elster, Arnold Neumaier. computing, 58(1):31-46, 1997. [doi]

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