Florian Buettner

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 36

Top Topics

Pitman Yor Process

Top Venues

Publications

Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner
Provably Better Explanations with Optimized Aggregation of Feature Attributions. CoRR (2024)
Thomas Decker, Alexander Koebler, Michael Lebacher, Ingo Thon, Volker Tresp, Florian Buettner
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. KDD (2024)
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 (2024)
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)
Giuseppe Serra, Florian Buettner
Federated Continual Learning Goes Online: Leveraging Uncertainty for Modality-Agnostic Class-Incremental Learning. CoRR (2024)
Giuseppe Serra, Ben Werner, Florian Buettner
How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning. CoRR (2024)
Sebastian Gruber, Florian Buettner
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. AISTATS (2023)
Arber Qoku, Florian Buettner
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity. AISTATS (2023)
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)
Achim Hekler, Titus J. Brinker, Florian Buettner
Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions. AAAI (2023)
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: Applications and New Frontiers of Generative Models for Healthcare. KDD (2023)
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)
Christian Tomani, Daniel Cremers, Florian Buettner
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. ECCV (13) (2022)
Sebastian G. Gruber, Florian Buettner
Better Uncertainty Calibration via Proper Scores for Classification and Beyond. NeurIPS (2022)
Arber Qoku, Florian Buettner
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity. CoRR (2022)
Sebastian Gruber, Florian Buettner
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. CoRR (2022)
Alexander Koebler, Ralf Gross, Florian Buettner, Ingo Thon
Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting. ECML/PKDD (6) (2022)
Sebastian Gruber, Florian Buettner
Trustworthy Deep Learning via Proper Calibration Errors: A Unifying Approach for Quantifying the Reliability of Predictive Uncertainty. CoRR (2022)
Christian Tomani, Daniel Cremers, Florian Buettner
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. CoRR (2021)
Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. CVPR (2021)
Yinchong Yang, Florian Buettner
Multi-output Gaussian Processes for uncertainty-aware recommender systems. UAI (2021)
Arber Qoku, Florian Buettner
Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables. CoRR (2021)
Christian Tomani, Florian Buettner
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. AAAI (2021)
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)
Xudong Sun, Florian Buettner
Hierarchical Domain Invariant Variational Auto-Encoding with weak domain supervision. CoRR (2021)
Yinchong Yang, Florian Buettner
Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems. CoRR (2021)
Florian Buettner, John Piorkowski, Ian McCulloh, Ulli Waltinger
AAAI FSS-19: Human-Centered AI: Trustworthiness of AI Models and Data Proceedings. CoRR (2020)
Christian Tomani, Florian Buettner
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. CoRR (2020)
Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner
TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification. ECAI (2020)
Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner
Post-hoc Uncertainty Calibration for Domain Drift Scenarios. CoRR (2020)
Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner
TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification. CoRR (2020)
Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze
Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior. ICLR (Poster) (2019)
Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze
Document Informed Neural Autoregressive Topic Models with Distributional Prior. AAAI (2019)
Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze
Document Informed Neural Autoregressive Topic Models with Distributional Prior. CoRR (2018)
Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schütze
textTOvec: Deep Contextualized Neural Autoregressive Models of Language with Distributed Compositional Prior. CoRR (2018)
Pankaj Gupta, Florian Buettner, Hinrich Schütze
Document Informed Neural Autoregressive Topic Models. CoRR (2018)
Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge, Aisha B. Miah, Kevin J. Harrington, Christopher M. Nutting
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)
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)