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Bayesian Inference

1724 directly classified papers

Papers per year

Papers

The neural dynamics of word recognition and integration EMNLP 2023
Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution CVPR 2023
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances ICML 2023
Thompson Sampling with Less Exploration is Fast and Optimal ICML 2023
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023
Gibbsian Polar Slice Sampling ICML 2023
Learning Treatment Effects from Observational and Experimental Data AISTATS 2023
Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning JMLR 2023
Leveraging Demonstrations to Improve Online Learning: Quality Matters ICML 2023
It’s MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk EMNLP 2023
Aligning Predictive Uncertainty with Clarification Questions in Grounded Dialog EMNLP 2023
Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding EMNLP 2023
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity AISTATS 2023
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation AAAI 2023
Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023
BETA-CD: A Bayesian Meta-Learned Cognitive Diagnosis Framework for Personalized Learning AAAI 2023
Compositional Score Modeling for Simulation-Based Inference ICML 2023
The Bayesian Learning Rule JMLR 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming ICML 2023
Divide-and-Conquer Fusion JMLR 2023
Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering JMLR 2023
Consistent Model-based Clustering using the Quasi-Bernoulli Stick-breaking Process JMLR 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023
Robust and Adaptive Deep Learning via Bayesian Principles AAAI 2023