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Bayesian Inference

1724 directly classified papers

Papers per year

Papers

Quantifying Contextual Aspects of Inter-annotator Agreement in Intertextuality Research EMNLP 2021
A Bayesian Framework for Information-Theoretic Probing EMNLP 2021
Bayesian Bellman Operators NIPS 2021
Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ICML 2021
Sparse Multi-Path Corrections in Fringe Projection Profilometry CVPR 2021
Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation ACL 2021
Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021
Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning ICML 2021
Posterior Meta-Replay for Continual Learning NIPS 2021
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation IJCNLP 2021
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates EACL 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions ICML 2021
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021
Mixed variable Bayesian optimization with frequency modulated kernels UAI 2021
Bayesian streaming sparse Tucker decomposition UAI 2021
Bayesian Quadrature on Riemannian Data Manifolds ICML 2021
pRSL: Interpretable multi-label stacking by learning probabilistic rules UAI 2021
Weighted model counting with conditional weights for Bayesian networks UAI 2021
Efficient debiased evidence estimation by multilevel Monte Carlo sampling UAI 2021
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling ICML 2021
Kernel Continual Learning ICML 2021
Safe Bayesian Optimisation for Controller Design by Utilising the Parameter Space Approach L4DC 2021
Bayesian Deep Learning via Subnetwork Inference ICML 2021