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Florian Buettner

19 papers · 2019–2026 · 9 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+8 more ↓ πŸ—ΊοΈ Taxonomy Completionist (43) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer πŸ”₯ Unstoppable Β· Bronze πŸ—ƒοΈ Keyword Collector (91) πŸ“ˆ Trend Setter

Venues

AAAI (4) AISTATS (4) CVPR (2) ICLR (2) ICML (2) UAI (2) ECCV (1) ICCV (1) NeurIPS (1)

Top co-authors

Christian Tomani (3) Thomas Decker (3) Sebastian Gruber (3) Sebastian Gregor Gruber (2) Alexander Koebler (2) Lukas Kuhn (2) Daniel Cremers (2) Pankaj Gupta (2) Yatin Chaudhary (2) Nassim Walha (2)

Research topics

Machine Learning (15) Artificial Intelligence (14) Optimization & Theory Β· Machine Learning (8) Core AI (7) Learning Types Β· Machine Learning (7) Bayesian & Probabilistic Β· Artificial Intelligence (6) Deep Learning (5) Application Areas (4) Core Methods (4) Natural Language Processing (3) Applications (3) Bayesian & Probabilistic Β· Machine Learning (3) Learning Types Β· Deep Learning (2) Models (2) Optimization & Theory Β· Deep Learning (2)

Keywords

uncertainty quantification (7) large language model (3) uncertainty estimation (2) proper score (2) domain shift (2) neural autoregressive model (2) calibration error (2) topic coherence (2) probabilistic prediction (2) post-hoc calibration (2) topic model (2) uncertainty calibration (2) collaborative filtering (1) model calibration (1) variational inference (1) epistemic uncertainty (1) online learning (1) representation learning (1) text classification (1) bayesian inference (1)

Papers

Eigenvalue Calibration for Semantic Embeddings of Large Language Models UAI 2026 Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach AAAI 2026 LVLM-Aided Alignment of Task-Specific Vision Models CVPR 2026 Efficient Unsupervised Shortcut Learning Detection and Mitigation in Transformers ICCV 2025 Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond ICLR 2025 Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention AISTATS 2025 A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models ICML 2024 Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors AISTATS 2024 Provably Better Explanations with Optimized Aggregation of Feature Attributions ICML 2024 Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity AISTATS 2023 Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions AAAI 2023 Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition AISTATS 2023 Better Uncertainty Calibration via Proper Scores for Classification and Beyond NeurIPS 2022 Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration ECCV 2022 Multi-output Gaussian Processes for uncertainty-aware recommender systems UAI 2021 Post-Hoc Uncertainty Calibration for Domain Drift Scenarios CVPR 2021 Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration AAAI 2021 Document Informed Neural Autoregressive Topic Models with Distributional Prior AAAI 2019 textTOvec: DEEP CONTEXTUALIZED NEURAL AUTOREGRESSIVE TOPIC MODELS OF LANGUAGE WITH DISTRIBUTED COMPOSITIONAL PRIOR ICLR 2019