| 2026 | AAAI | Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach. | Nassim Walha, Sebastian G. Gruber, Thomas Decker, Yinchong Yang, Alireza Javanmardi, Eyke Hllermeier, Florian Buettner |
| 2025 | AISTATS | Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention. | Alexander Koebler, Thomas Decker, Ingo Thon, Volker Tresp, Florian Buettner |
| 2025 | ICCV | Efficient Unsupervised Shortcut Learning Detection and Mitigation in Transformers. | Lukas Kuhn, Sari Sadiya, Jrg Schltterer, Florian Buettner, Christin Seifert, Gemma Roig |
| 2025 | ICLR | Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond. | Giuseppe Serra, Florian Buettner |
| 2024 | HCI | Through the Eyes of the Expert: Aligning Human and Machine Attention for Industrial AI. | Alexander Koebler, Christian Greisinger, Jan Paulus, Ingo Thon, Florian Buettner |
| 2024 | ICDM | MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model. | Alexander Koebler, Ingo Thon, Florian Buettner |
| 2024 | ICML | Provably Better Explanations with Optimized Aggregation of Feature Attributions. | Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner |
| 2024 | ICML | A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models. | Sebastian Gregor Gruber, Florian Buettner |
| 2024 | KDD | Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. | Thomas Decker, Alexander Koebler, Michael Lebacher, Ingo Thon, Volker Tresp, Florian Buettner |
| 2023 | AAAI | Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions. | Achim Hekler, Titus J. Brinker, Florian Buettner |
| 2023 | AISTATS | Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition. | Sebastian Gruber, Florian Buettner |
| 2023 | AISTATS | Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity. | Arber Qoku, Florian Buettner |
| 2023 | KDD | Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare. | Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner |
| 2022 | ECCV | Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. | Christian Tomani, Daniel Cremers, Florian Buettner |
| 2022 | KDD | Workshop on Applied Data Science for Healthcare (DSHealth): Transparent and Human-centered AI. | Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner |
| 2021 | AAAI | Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. | Christian Tomani, Florian Buettner |
| 2021 | CVPR | Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. | Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner |
| 2021 | KDD | 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. | Fei Wang, Prithwish Chakraborty, Tao Xu, Pei-Yun Sabrina Hsueh, Xudong Sun, Gregor Stiglic, Gracy Crane, Jiang Bian, Laleh Haghverdi, Lixia Yao, Florian Buettner |
| 2021 | UAI | Multi-output Gaussian Processes for uncertainty-aware recommender systems. | Yinchong Yang, Florian Buettner |
| 2020 | ECAI | TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification. | Yushan Liu, Markus M. Geipel, Christoph Tietz, Florian Buettner |
| 2019 | AAAI | Document Informed Neural Autoregressive Topic Models with Distributional Prior. | Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schtze |
| 2019 | ICLR | Texttovec: Deep Contextualized Neural autoregressive Topic Models of Language with Distributed Compositional Prior. | Pankaj Gupta, Yatin Chaudhary, Florian Buettner, Hinrich Schtze |
| 2010 | ICMLA | 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. | Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge, Aisha B. Miah, Kevin J. Harrington, Christopher M. Nutting |
| 2009 | ICMLA | Using Bayesian Logistic Regression with High-Order Interactions to Model Radiation-Induced Toxicities Following Radiotherapy. | Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge |