Beate Sick

31 papers A* 1A 1B 1C 1Journal 22Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep interpretable ensembles.
Neurocomputing
Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
2025 J jnl
Going beyond explainability in multi-modal stroke outcome prediction models.
CoRR
Jonas Brändli, Maurice Schneeberger, Lisa Herzog, Loran Avci, Nordin Dari, Martin Häansel, Hakim Baazaoui, Pascal Bühler, Susanne Wegener, Beate Sick
2025 — conf
Interpretable Neural Causal Models with TRAM-DAGs.
CLeaR
Beate Sick, Oliver Dürr
2025 J jnl
Interpretable Neural Causal Models with TRAM-DAGs.
CoRR
Beate Sick, Oliver Dürr
2025 — conf
Outcome Prediction and Individualized Treatment Effect Estimation in Patients with Large Vessel Occlusion Stroke.
SWITCH@MICCAI
Lisa Herzog, Pascal Bühler, Ezequiel de la Rosa, Beate Sick, Susanne Wegener
2025 J jnl
Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke.
CoRR
Lisa Herzog, Pascal Bühler, Ezequiel de la Rosa, Beate Sick, Susanne Wegener
2024 A conf
Bayesian Semi-structured Subspace Inference.
AISTATS
Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
2024 J jnl
Bayesian Semi-structured Subspace Inference.
CoRR
Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
2024 J jnl
Estimating Conditional Distributions with Neural Networks Using
J. Stat. Softw.
Lucas Kook, Philipp F. M. Baumann, Oliver Dürr, Beate Sick, David Rügamer
2024 J jnl
Large language models to process, analyze, and synthesize biomedical texts: a scoping review.
Discov. Artif. Intell.
Simona Doneva, Sijing Qin, Beate Sick, Tilia Ellendorff, Jean-Philippe Goldman, Gerold Schneider, Benjamin Ineichen
2024 A* conf
NeuroTrialNER: An Annotated Corpus for Neurological Diseases and Therapies in Clinical Trial Registries.
EMNLP
Simona Doneva, Tilia Ellendorff, Beate Sick, Jean-Philippe Goldman, Amelia Cannon, Gerold Schneider, Benjamin Ineichen
2023 J jnl
Short-Term Density Forecasting of Low-Voltage Load Using Bernstein-Polynomial Normalizing Flows.
IEEE Trans. Smart Grid
Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
2023 J jnl
Single-shot Bayesian approximation for neural networks.
CoRR
Kai Brach, Beate Sick, Oliver Dürr
2022 J jnl
Bernstein Flows for Flexible Posteriors in Variational Bayes.
CoRR
Oliver Dürr, Stephan Hörling, Daniel Dold, Ivonne Kovylov, Beate Sick
2022 J jnl
Deep and interpretable regression models for ordinal outcomes.
Pattern Recognit.
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
2022 J jnl
Deep interpretable ensembles.
CoRR
Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
2022 J jnl
Distributional anchor regression.
Stat. Comput.
Lucas Kook, Beate Sick, Peter Bühlmann
2022 J jnl
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows.
CoRR
Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
2021 J jnl
Transformation Models for Flexible Posteriors in Variational Bayes.
CoRR
Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick
2020 B conf
Deep transformation models: Tackling complex regression problems with neural network based transformation models.
ICPR
Beate Sick, Torsten Hothorn, Oliver Dürr
2020 J jnl
Deep transformation models: Tackling complex regression problems with neural network based transformation models.
CoRR
Beate Sick, Torsten Hothorn, Oliver Dürr
2020 J jnl
Integrating uncertainty in deep neural networks for MRI based stroke analysis.
CoRR
Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
2020 J jnl
Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical Image Anal.
Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
2020 J jnl
Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes.
CoRR
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
2020 J jnl
Single Shot MC Dropout Approximation.
CoRR
Kai Brach, Beate Sick, Oliver Dürr
2019 — ch.
Beyond ImageNet: Deep Learning in Industrial Practice.
Applied Data Science
Thilo Stadelmann, Vasily Tolkachev, Beate Sick, Jan Stampfli, Oliver Dürr
2019 J jnl
Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks.
Comput. Electr. Eng.
Janick Rohrbach, Tobias Reinhard, Beate Sick, Oliver Dürr
2009 — conf
Practical Quality Assessment of Microarray Data by Simulation of Differential Gene Expression.
ISBRA
Brian E. Howard, Beate Sick, Steffen Heber
2009 J jnl
Unsupervised assessment of microarray data quality using a Gaussian mixture model.
BMC Bioinform.
Brian E. Howard, Beate Sick, Steffen Heber
2007 C conf
Quality Assessment of Affymetrix GeneChip Data using the EM Algorithm and a Naive Bayes Classifier.
BIBE
Brian E. Howard, Beate Sick, Imara Perera, Yang Ju Im, Heike Winter-Sederoff, Steffen Heber
2006 — conf
Automatic quality assessment of Affymetrix GeneChip data.
ACM Southeast Regional Conference
Steffen Heber, Beate Sick