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Pattern Recognition: 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings

2024

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Inference of cosmic-ray source properties by conditional invertible neural networks

The European physical journal. C, Particles and fields, 2022-02, Vol.82 (2), p.1-10, Article 171

2022

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OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

PLoS computational biology, 2021-10, Vol.17 (10), p.e1009472-e1009472

2021

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Invertible networks or partons to detector and back again

SciPost physics, 2020-11, Vol.9 (5), p.074, Article 074

2020

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Neural superstatistics for Bayesian estimation of dynamic cognitive models

Scientific reports, 2023-08, Vol.13 (1), p.13778-13778, Article 13778

2023

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Measuring QCD Splittings with Invertible Networks

SciPost physics, 2021-06, Vol.10 (6), p.126, Article 126

2021

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Toward Digital Staining using Imaging Mass Spectrometry and Random Forests

Journal of proteome research, 2009-07, Vol.8 (7), p.3558-3567

2009

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Towards learned emulation of interannual water isotopologue variations in General Circulation Models

Environmental Data Science, 2023, Vol.2, Article e35

2023

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Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images

Analytical chemistry (Washington), 2013-01, Vol.85 (1), p.147-155

2013

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Applications of Discrete Geometry and Mathematical Morphology: First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers

1, 2012

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Pattern Recognition: 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19–22, 2023, Proceedings

2024

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Long short‐term memory networks for proton dose calculation in highly heterogeneous tissues

Medical physics (Lancaster), 2021-04, Vol.48 (4), p.1893-1908

2021

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Applications of Discrete Geometry and Mathematical Morphology: First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers

2012

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Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study

Investigative radiology, 2019-10, Vol.54 (10), p.653-660

2019

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Towards end‐to‐end likelihood‐free inference with convolutional neural networks

British journal of mathematical & statistical psychology, 2020-02, Vol.73 (1), p.23-43

2020

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OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

PLoS computational biology, 2021-10, Vol.17 (10), p.e1009472

2021

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Data Resource Profile: The Global School-based Student Health Survey—behavioural risk and protective factors among adolescents

International journal of epidemiology, 2023-04, Vol.52 (2), p.e102-e109

2023

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Virtual Raters for Reproducible and Objective Assessments in Radiology

Scientific reports, 2016-04, Vol.6 (1), p.25007-25007, Article 25007

2016

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BayesFlow: Amortized Bayesian Workflows With Neural Networks

Journal of open source software, 2023-09, Vol.8 (89), p.5702

2023

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Conditional Invertible Neural Networks for Diverse Image-to-Image Translation

Pattern Recognition, 2021, Vol.12544, p.373-387

2021

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Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions

Cancers, 2021-06, Vol.13 (13), p.3108

2021

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Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras

Optical engineering, 2009-01, Vol.48 (1), p.13602

Plaue, Matthias

2009

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Learning Robust Models Using the Principle of Independent Causal Mechanisms

Pattern Recognition, 2022, Vol.13024, p.79-110

2022

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XPMaps and Topological Segmentation — A Unified Approach to Finite Topologies in the Plane

Discrete Geometry for Computer Imagery, 2002, Vol.2301, p.22-33

2002

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Riemannian SOS-Polynomial Normalizing Flows

Pattern Recognition, 2021, Vol.12544, p.218-231

2021

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Pattern Recognition: 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings

Inference of cosmic-ray source properties by conditional invertible neural networks

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

Invertible networks or partons to detector and back again

Neural superstatistics for Bayesian estimation of dynamic cognitive models

Measuring QCD Splittings with Invertible Networks

Toward Digital Staining using Imaging Mass Spectrometry and Random Forests

Towards learned emulation of interannual water isotopologue variations in General Circulation Models

Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images

Applications of Discrete Geometry and Mathematical Morphology: First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers

Pattern Recognition: 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19–22, 2023, Proceedings

Long short‐term memory networks for proton dose calculation in highly heterogeneous tissues

Applications of Discrete Geometry and Mathematical Morphology: First International Workshop, WADGMM 2010, Istanbul, Turkey, August 22, 2010, Revised Selected Papers

Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study

Towards end‐to‐end likelihood‐free inference with convolutional neural networks

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

Data Resource Profile: The Global School-based Student Health Survey—behavioural risk and protective factors among adolescents

Virtual Raters for Reproducible and Objective Assessments in Radiology

BayesFlow: Amortized Bayesian Workflows With Neural Networks

Conditional Invertible Neural Networks for Diverse Image-to-Image Translation

Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions

Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras

Learning Robust Models Using the Principle of Independent Causal Mechanisms

XPMaps and Topological Segmentation — A Unified Approach to Finite Topologies in the Plane

Riemannian SOS-Polynomial Normalizing Flows

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