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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Bayesian Meta-Analyses Could Be More: A Case Study in Trial of Labor After a Cesarean-section Outcomes and Complications AAAI 2026
BayesVQA: Energy-Guided Bayesian Debiasing for Language-Bias-Robust Visual Question Answering AAAI 2026
BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models AAAI 2026
GEM: Generative Entropy-Guided Preference Modeling for Few-Shot Alignment of LLMs AAAI 2026
MetaGameBO: Hierarchical Game-Theoretic Driven Robust Meta-Learning for Bayesian Optimization AAAI 2026
Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach AAAI 2026
Sparse Poisson Gamma Belief Networks for High-Dimensional Sparse Count Data AAAI 2026
Bayesian Network Structural Consensus via Greedy Min-Cut Analysis AAAI 2026
GeoBayes: Probabilistic Image Geo-Localization Inference via Sequential Bayesian Updating AAAI 2026
Rethinking Label Consistency of In-Context Learning: An Implicit Transductive Label Propagation Perspective AAAI 2026
Causal Inference Under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects AAAI 2026
BayesAgent: Bayesian Agentic Reasoning Under Uncertainty via Verbalized Probabilistic Graphical Modeling AAAI 2026
SGPMIL: Sparse Gaussian Process Multiple Instance Learning WACV 2026
Learning Label Distribution with Dirichlet Process Mixture Model AAAI 2026
Bayesian Neural Networks for One-to-Many Mapping in Image Enhancement AAAI 2026
SEA-PACE: Semi-Supervised Underwater Image Enhancement via Gaussian Process–Assisted Self-Paced Learning AAAI 2026
TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models AAAI 2026
Learning-Augmented Ski Rental with Discrete Distribution: A Bayesian Approach AAAI 2026
Life, Machine Learning, and the Search for Habitability: Predicting Biosignature Fluxes for the Habitable Worlds Observatory AAAI 2026
Scalability of Bayesian Network Structure Elicitation with Large Language Models: a Novel Methodology and Comparative Analysis COLING 2025
On Evaluating LLMs’ Capabilities as Functional Approximators: A Bayesian Evaluation Framework COLING 2025
Uncertainty Modelling in Under-Represented Languages with Bayesian Deep Gaussian Processes COLING 2025
DAGs as Minimal I-maps for the Induced Models of Causal Bayesian Networks under Conditioning JMLR 2025
Towards Uncertainty Unification: A Case Study for Preference Learning RSS 2025
NUTMEG: Separating Signal From Noise in Annotator Disagreement EMNLP 2025