Beate Sick

发表

Beyond ImageNet: Deep Learning in Industrial Practice

Thilo Stadelmann, Vasily Tolkachev, Beate Sick, 2019, Applied Data Science.

Modeling writing phases : interdisciplinary method building – an interim report

Beate Sick, Daniel Perrin, Mathias Fürer, 2012 .

Developing Deep Learning Applications for Life Science and Pharma Industry

Vasily Tolkachev, Beate Sick, Stephan Heyse, 2018, Drug Research.

Unsupervised assessment of microarray data quality using a Gaussian mixture model

Beate Sick, Brian E. Howard, Steffen Heber, 2009, BMC Bioinformatics.

From walking to jumping : statistical modeling of writing processes

Marc Wildi, Daniel Perrin, Beate Sick, 2011 .

Single Shot MC Dropout Approximation pdf

Beate Sick, Oliver Dürr, Kai Brach, 2020, ArXiv.

A New Method for Travel Time Estimation on Long Freeway Sections

Albert Steiner, Beate Sick, A. Steiner, 2008, European Journal of Transport and Infrastructure Research.

Integrating uncertainty in deep neural networks for MRI based stroke analysis

Beate Sick, Susanne Wegener, Lisa Herzog, 2020, Medical Image Anal..

P16.32TOWARDS COMPUTER AIDED NEURORADIOLOGICAL DIAGNOSTICS OF BRAIN TUMORS

Stefan Bauer, Beate Sick, Roland Wiest, 2014 .

RACE: Remote Analysis Computation for gene Expression data

Beate Sick, Gnanasekaran Thoppae, Steffen Heber, 2005, Nucleic Acids Res..

Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes pdf

Torsten Hothorn, Beate Sick, Oliver Dürr, 2020, ArXiv.

Automatic quality assessment of Affymetrix GeneChip data

Beate Sick, Steffen Heber, 2006, ACM-SE 44.

Practical Quality Assessment of Microarray Data by Simulation of Differential Gene Expression

Beate Sick, Brian E. Howard, Steffen Heber, 2009, ISBRA.

Quality Assessment of Affymetrix GeneChip Data using the EM Algorithm and a Naive Bayes Classifier

Beate Sick, Brian E. Howard, Steffen Heber, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

Deep transformation models: Tackling complex regression problems with neural network based transformation models pdf

Torsten Hothorn, Beate Sick, Oliver Dürr, 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes.

Vasily Tolkachev, Beate Sick, Oliver Dürr, 2018, Assay and drug development technologies.

Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks

Tobias Reinhard, Beate Sick, Oliver Dürr, 2019, Comput. Electr. Eng..

Quality assessment of Affymetrix GeneChip data.

Beate Sick, Steffen Heber, S. Heber, 2006, Omics : a journal of integrative biology.

Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks

Beate Sick, Oliver Dürr, O. Dürr, 2016, Journal of biomolecular screening.

Quality Assessment ofAffymetrix GeneChip Data usingtheEM Algorithm and aNaiveBayes Classifier

Beate Sick, Steffen Heber, S. Heber, 2009 .

Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes

Torsten Hothorn, Beate Sick, Oliver Dürr, 2022, Pattern Recognit..

Distributional Anchor Regression

Beate Sick, Peter Buhlmann, Lucas Kook, 2021 .

Transformation Models for Flexible Posteriors in Variational Bayes pdf

Beate Sick, Oliver Dürr, Sefan Hörtling, 2021, ArXiv.

Dysregulation of Gene Expression in Primary Neuron Models of Huntington's Disease Shows That Polyglutamine-Related Effects on the Striatal Transcriptome May Not Be Dependent on Brain Circuitry

Beate Sick, Ruth Luthi-Carter, Patrick Aebischer, 2008, The Journal of Neuroscience.