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2020 – today
- 2024
[c10]Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr:
Bayesian Semi-structured Subspace Inference. AISTATS 2024: 1819-1827- [i12]Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr:
Bayesian Semi-structured Subspace Inference. CoRR abs/2401.12950 (2024) - 2023
- [j4]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): 4902-4911 (2023) - [i11]Oliver Dürr, Po-Yu Fan, Zong-Xian Yin:
Bayesian Calibration of MEMS Accelerometers. CoRR abs/2306.06144 (2023) - [i10]Kai Brach, Beate Sick, Oliver Dürr:
Single-shot Bayesian approximation for neural networks. CoRR abs/2308.12785 (2023) - 2022
- [j3]Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick:
Deep and interpretable regression models for ordinal outcomes. Pattern Recognit. 122: 108263 (2022) - [i9]Oliver Dürr, Stephan Hörling, Daniel Dold, Ivonne Kovylov, Beate Sick:
Bernstein Flows for Flexible Posteriors in Variational Bayes. CoRR abs/2202.05650 (2022) - [i8]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 abs/2204.13939 (2022) - 2021
- [i7]Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick:
Transformation Models for Flexible Posteriors in Variational Bayes. CoRR abs/2106.00528 (2021) - 2020
- [j2]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: 101790 (2020) - [c9]Beate Sick, Torsten Hothorn, Oliver Dürr:
Deep transformation models: Tackling complex regression problems with neural network based transformation models. ICPR 2020: 2476-2481 - [i6]Beate Sick, Torsten Hothorn, Oliver Dürr:
Deep transformation models: Tackling complex regression problems with neural network based transformation models. CoRR abs/2004.00464 (2020) - [i5]Kai Brach, Beate Sick, Oliver Dürr:
Single Shot MC Dropout Approximation. CoRR abs/2007.03293 (2020) - [i4]Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick:
Integrating uncertainty in deep neural networks for MRI based stroke analysis. CoRR abs/2008.06332 (2020) - [i3]Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick:
Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes. CoRR abs/2010.08376 (2020)
2010 – 2019
- 2019
- [j1]Janick Rohrbach, Tobias Reinhard, Beate Sick, Oliver Dürr:
Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks. Comput. Electr. Eng. 78: 472-481 (2019) - [p1]Thilo Stadelmann, Vasily Tolkachev, Beate Sick, Jan Stampfli, Oliver Dürr:
Beyond ImageNet: Deep Learning in Industrial Practice. Applied Data Science 2019: 205-232 - 2018
- [c8]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Dürr, Thilo Stadelmann:
Learning Neural Models for End-to-End Clustering. ANNPR 2018: 126-138 - [c7]Thilo Stadelmann, Sebastian Glinski-Haefeli, Patrick Gerber, Oliver Dürr:
Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering. ANNPR 2018: 333-345 - [i2]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Durr, Thilo Stadelmann:
Learning Neural Models for End-to-End Clustering. CoRR abs/1807.04001 (2018) - 2017
- [c6]Yanick X. Lukic, Carlo Vogt, Oliver Durr, Thilo Stadelmann:
Learning embeddings for speaker clustering based on voice equality. MLSP 2017: 1-6 - 2016
- [c5]Yanick X. Lukic, Carlo Vogt, Oliver Durr, Thilo Stadelmann:
Speaker identification and clustering using convolutional neural networks. MLSP 2016: 1-6 - 2015
- [c4]Oliver Dürr, Yves Pauchard, Diego Browarnik, Rebekka Axthelm, Martin Loeser:
Deep Learning on a Raspberry Pi for Real Time Face Recognition. Eurographics (Posters) 2015: 11-12 - 2014
- [c3]Mark Cieliebak, Oliver Dürr, Fatih Uzdilli:
Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools. LREC 2014: 3100-3104 - [c2]Oliver Dürr, Fatih Uzdilli, Mark Cieliebak:
JOINT_FORCES: Unite Competing Sentiment Classifiers with Random Forest. SemEval@COLING 2014: 366-369 - 2013
- [c1]Mark Cieliebak, Oliver Dürr, Fatih Uzdilli:
Potential and Limitations of Commercial Sentiment Detection Tools. ESSEM@AI*IA 2013: 47-58 - 2012
- [i1]Oliver Dürr, Arnd Brandenburg:
Using Community Structure for Complex Network Layout. CoRR abs/1207.6282 (2012)
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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