Florian Buettner
17 papers · 2019–2026 · 9 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (6) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird
🌍
Conference Polyglot
(9)
🏃
Academic Marathon
(6)
🏆
Keyword Champion
(2)
🏆
Grand Slam
🗃️
Keyword Collector
(60)
💎
Century Club
(16)
🔥
Unstoppable
(5)
📈
Trend Setter
🚀
Conference Pioneer
Conferences
AAAI (4)
AISTATS (4)
ICLR (2)
ICML (2)
CVPR (1)
ECCV (1)
ICCV (1)
NIPS (1)
UAI (1)
Top co-authors
Research topics
Keywords
uncertainty quantification
(5)
post-hoc calibration
(2)
proper score
(2)
uncertainty calibration
(2)
domain shift
(2)
probabilistic prediction
(2)
calibration error
(2)
text classification
(1)
bayesian inference
(1)
shortcut learning
(1)
bregman divergence
(1)
collaborative filtering
(1)
document modeling
(1)
structured sparsity
(1)
model calibration
(1)
domain adaptation
(1)
horseshoe prior
(1)
neural autoregressive model
(1)
topic model
(1)
epistemic uncertainty
(1)
Papers
Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach
AAAI 2026
Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
ICLR 2025
Efficient Unsupervised Shortcut Learning Detection and Mitigation in Transformers
ICCV 2025
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
AISTATS 2025
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors
AISTATS 2024
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
ICML 2024
Provably Better Explanations with Optimized Aggregation of Feature Attributions
ICML 2024
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition
AISTATS 2023
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
Better Uncertainty Calibration via Proper Scores for Classification and Beyond
NIPS 2022
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration
ECCV 2022
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios
CVPR 2021
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration
AAAI 2021
Multi-output Gaussian Processes for uncertainty-aware recommender systems
UAI 2021
textTOvec: DEEP CONTEXTUALIZED NEURAL AUTOREGRESSIVE TOPIC MODELS OF LANGUAGE WITH DISTRIBUTED COMPOSITIONAL PRIOR
ICLR 2019
Document Informed Neural Autoregressive Topic Models with Distributional Prior
AAAI 2019