Beate Sick

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 17

Top Topics

Transformation Models

Top Venues

Pattern Recognit.

Medical Image Anal.

Publications

Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
Bayesian Semi-structured Subspace Inference. AISTATS (2024)
Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
Bayesian Semi-structured Subspace Inference. CoRR (2024)
Kai Brach, Beate Sick, Oliver Dürr
Single-shot Bayesian approximation for neural networks. CoRR (2023)
Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
Short-Term Density Forecasting of Low-Voltage Load Using Bernstein-Polynomial Normalizing Flows. IEEE Trans. Smart Grid 14 (6) (2023)
Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
Deep interpretable ensembles. CoRR (2022)
Lucas Kook, Beate Sick, Peter Bühlmann
Distributional anchor regression. Stat. Comput. 32 (3) (2022)
Oliver Dürr, Stephan Hörling, Daniel Dold, Ivonne Kovylov, Beate Sick
Bernstein Flows for Flexible Posteriors in Variational Bayes. CoRR (2022)
Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows. CoRR (2022)
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
Deep and interpretable regression models for ordinal outcomes. Pattern Recognit. 122 (2022)
Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick
Transformation Models for Flexible Posteriors in Variational Bayes. CoRR (2021)
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes. CoRR (2020)
Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
Integrating uncertainty in deep neural networks for MRI based stroke analysis. CoRR (2020)
Kai Brach, Beate Sick, Oliver Dürr
Single Shot MC Dropout Approximation. CoRR (2020)
Beate Sick, Torsten Hothorn, Oliver Dürr
Deep transformation models: Tackling complex regression problems with neural network based transformation models. ICPR (2020)
Beate Sick, Torsten Hothorn, Oliver Dürr
Deep transformation models: Tackling complex regression problems with neural network based transformation models. CoRR (2020)
Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
Integrating uncertainty in deep neural networks for MRI based stroke analysis. Medical Image Anal. 65 (2020)
Janick Rohrbach, Tobias Reinhard, Beate Sick, Oliver Dürr
Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks. Comput. Electr. Eng. 78 (2019)
Brian E. Howard, Beate Sick, Steffen Heber
Practical Quality Assessment of Microarray Data by Simulation of Differential Gene Expression. ISBRA (2009)
Brian E. Howard, Beate Sick, Steffen Heber
Unsupervised assessment of microarray data quality using a Gaussian mixture model. BMC Bioinform. 10 (2009)
Brian E. Howard, Beate Sick, Imara Perera, Yang Ju Im, Heike Winter-Sederoff, Steffen Heber
Quality Assessment of Affymetrix GeneChip Data using the EM Algorithm and a Naive Bayes Classifier. BIBE (2007)
Steffen Heber, Beate Sick
Automatic quality assessment of Affymetrix GeneChip data. ACM Southeast Regional Conference (2006)
Michael Psarros, Steffen Heber, Manuela Sick, Gnanasekaran Thoppae, Keith Harshman, Beate Sick
: Remote Analysis Computation for gene Expression data. Nucleic Acids Res. 33 (Web-Server-Issue) (2005)