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Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity


Apr 13, 2022
Arber Qoku, Florian Buettner

* 10 pages, 5 figures 

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Trustworthy Deep Learning via Proper Calibration Errors: A Unifying Approach for Quantifying the Reliability of Predictive Uncertainty


Mar 15, 2022
Sebastian Gruber, Florian Buettner


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Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables


Jul 08, 2021
Arber Qoku, Florian Buettner

* 5 pages, 6 figures, Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare 

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Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems


Jun 08, 2021
Yinchong Yang, Florian Buettner


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Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration


Feb 24, 2021
Christian Tomani, Daniel Cremers, Florian Buettner

* Technical report 

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Hierarchical Variational Auto-Encoding for Unsupervised Domain Generalization


Feb 22, 2021
Xudong Sun, Florian Buettner


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Hierarchical Domain Invariant Variational Auto-Encoding with weak domain supervision


Jan 23, 2021
Xudong Sun, Florian Buettner


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Post-hoc Uncertainty Calibration for Domain Drift Scenarios


Dec 20, 2020
Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner

* Technical report 

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Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration


Dec 20, 2020
Christian Tomani, Florian Buettner

* Accepted to AAAI 2021. Code available at https://github.com/tochris/falcon 

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TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification


Jul 10, 2020
Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner

* Accepted at ECAI 2020 (24th European Conference on Artificial Intelligence) 

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