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Florian Buettner 0001
Person information
- affiliation: Goethe University Frankfurt, Germany
- affiliation: German Cancer Research Center (DKFZ), Germany
- affiliation: German Cancer Consortium (DKTK), Germany
Other persons with the same name
- Florian A. Büttner
(aka: Florian Buettner 0002) — Helmholtz Zentrum München, Institute of Computational Biology, Munich, Germany
- Florian Büttner 0002 — Technische Hochschule Nürnberg, Germany
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2020 – today
- 2024
- [c23]Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko:
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. AISTATS 2024: 3466-3474 - [c22]Alexander Koebler, Christian Greisinger, Jan Paulus, Ingo Thon, Florian Buettner:
Through the Eyes of the Expert: Aligning Human and Machine Attention for Industrial AI. HCI (52) 2024: 407-423 - [c21]Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner:
Provably Better Explanations with Optimized Aggregation of Feature Attributions. ICML 2024 - [c20]Sebastian Gregor Gruber, Florian Buettner:
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models. ICML 2024 - [c19]Thomas Decker
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. KDD 2024: 550-561 - [i24]Xudong Sun, Carla Feistner, Alexej Gossmann, George Schwarz, Rao Muhammad Umer, Lisa Beer, Patrick Rockenschaub, Rahul Babu Shrestha, Armin Gruber, Nutan Chen, Sayedali Shetab Boushehri, Florian Buettner, Carsten Marr:
DomainLab: A modular Python package for domain generalization in deep learning. CoRR abs/2403.14356 (2024) - [i23]Giuseppe Serra, Florian Buettner:
Federated Continual Learning Goes Online: Leveraging Uncertainty for Modality-Agnostic Class-Incremental Learning. CoRR abs/2405.18925 (2024) - [i22]Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner:
Provably Better Explanations with Optimized Aggregation of Feature Attributions. CoRR abs/2406.05090 (2024) - [i21]Giuseppe Serra, Ben Werner, Florian Buettner:
How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning. CoRR abs/2407.07668 (2024) - [i20]Thomas Decker, Alexander Koebler, Michael Lebacher, Ingo Thon, Volker Tresp, Florian Buettner:
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. CoRR abs/2408.13648 (2024) - [i19]Sebastian G. Gruber, Pascal Tobias Ziegler, Florian Buettner:
Disentangling Mean Embeddings for Better Diagnostics of Image Generators. CoRR abs/2409.01314 (2024) - 2023
- [c18]Achim Hekler, Titus J. Brinker, Florian Buettner:
Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions. AAAI 2023: 14856-14864 - [c17]Sebastian Gruber, Florian Buettner:
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. AISTATS 2023: 11331-11354 - [c16]Arber Qoku, Florian Buettner:
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity. AISTATS 2023: 11545-11562 - [c15]Tao Xu
Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare. KDD 2023: 5893-5894 - [c14]Michela Destito, Paolo Zaffino, Jolanda Sabatino, Claudia Critelli, Arber Qoku, Florian Buettner, Salvatore De Rosa, Maria Francesca Spadea:
Deep Learning Model for Video-Classification of Echocardiography Images. MetroXRAINE 2023: 479-483 - [i18]Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - [i17]Tim J. Adler, Jan-Hinrich Nölke
Application-driven Validation of Posteriors in Inverse Problems. CoRR abs/2309.09764 (2023) - [i16]Sebastian G. Gruber, Florian Büttner:
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models. CoRR abs/2310.05833 (2023) - [i15]Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. CoRR abs/2312.08589 (2023) - 2022
- [c13]Christian Tomani, Daniel Cremers
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. ECCV (13) 2022: 555-569 - [c12]Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner:
Workshop on Applied Data Science for Healthcare (DSHealth): Transparent and Human-centered AI. KDD 2022: 4908-4909 - [c11]Sebastian G. Gruber, Florian Buettner:
Better Uncertainty Calibration via Proper Scores for Classification and Beyond. NeurIPS 2022 - [c10]Alexander Koebler, Ralf Gross, Florian Buettner, Ingo Thon:
Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting. ECML/PKDD (6) 2022: 219-235 - [i14]Sebastian G. Gruber, Florian Buettner:
Trustworthy Deep Learning via Proper Calibration Errors: A Unifying Approach for Quantifying the Reliability of Predictive Uncertainty. CoRR abs/2203.07835 (2022) - [i13]Arber Qoku, Florian Buettner:
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity. CoRR abs/2204.06242 (2022) - [i12]Sebastian G. Gruber, Florian Buettner:
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. CoRR abs/2210.12256 (2022) - 2021
- [c9]Christian Tomani, Florian Buettner:
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. AAAI 2021: 9886-9896 - [c8]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. CVPR 2021: 10124-10132 - [c7]Fei Wang, Prithwish Chakraborty, Tao Xu, Pei-Yun Sabrina Hsueh, Xudong Sun, Gregor Stiglic, Gracy Crane, Jiang Bian, Laleh Haghverdi, Lixia Yao, Florian Buettner:
KDD Health Day/DSHealth 2021: Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare: State of XAI and Trustworthiness in Health. KDD 2021: 4159-4160 - [c6]Yinchong Yang, Florian Buettner:
Multi-output Gaussian Processes for uncertainty-aware recommender systems. UAI 2021: 1505-1514 - [i11]Xudong Sun, Florian Buettner:
Hierarchical Domain Invariant Variational Auto-Encoding with weak domain supervision. CoRR abs/2101.09436 (2021) - [i10]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. CoRR abs/2102.12182 (2021) - [i9]Yinchong Yang, Florian Buettner:
Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems. CoRR abs/2106.04221 (2021) - [i8]Arber Qoku, Florian Buettner:
Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables. CoRR abs/2107.03730 (2021) - 2020
- [c5]Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner:
TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification. ECAI 2020: 1858-1865 - [i7]Florian Buettner, John Piorkowski, Ian McCulloh, Ulli Waltinger:
AAAI FSS-19: Human-Centered AI: Trustworthiness of AI Models and Data Proceedings. CoRR abs/2001.05375 (2020) - [i6]Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner:
TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification. CoRR abs/2007.05307 (2020) - [i5]Christian Tomani, Florian Buettner:
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. CoRR abs/2012.10923 (2020) - [i4]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-hoc Uncertainty Calibration for Domain Drift Scenarios. CoRR abs/2012.10988 (2020)
2010 – 2019
- 2019
- [c4]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
Document Informed Neural Autoregressive Topic Models with Distributional Prior. AAAI 2019: 6505-6512 - [c3]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior. ICLR (Poster) 2019 - 2018
- [i3]Pankaj Gupta, Florian Buettner, Hinrich Schütze:
Document Informed Neural Autoregressive Topic Models. CoRR abs/1808.03793 (2018) - [i2]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
Document Informed Neural Autoregressive Topic Models with Distributional Prior. CoRR abs/1809.06709 (2018) - [i1]Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze:
textTOvec: Deep Contextualized Neural Autoregressive Models of Language with Distributed Compositional Prior. CoRR abs/1810.03947 (2018) - 2010
- [c2]Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge, Aisha B. Miah, Kevin J. Harrington
Using a Bayesian Feature-selection Algorithm to Identify Dose-response Models Based on the Shape of the 3D Dose-distribution: An Example from a Head-and-neck Cancer Trial. ICMLA 2010: 740-745
2000 – 2009
- 2009
- [c1]Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge:
Using Bayesian Logistic Regression with High-Order Interactions to Model Radiation-Induced Toxicities Following Radiotherapy. ICMLA 2009: 451-456
Coauthor Index
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