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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Misspecified Gaussian Process Bandit Optimization NIPS 2021
Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization AAAI 2021
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification NIPS 2021
Repulsive Deep Ensembles are Bayesian NIPS 2021
Truncated Marginal Neural Ratio Estimation NIPS 2021
Entropy-based adaptive Hamiltonian Monte Carlo NIPS 2021
Marginalised Gaussian Processes with Nested Sampling NIPS 2021
Meta-Learning Reliable Priors in the Function Space NIPS 2021
Probability Paths and the Structure of Predictions over Time NIPS 2021
Efficient Bayesian network structure learning via local Markov boundary search NIPS 2021
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain NIPS 2021
Black-box density function estimation using recursive partitioning ICML 2021
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning NIPS 2021
Infinite Time Horizon Safety of Bayesian Neural Networks NIPS 2021
Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract) AAAI 2021
Learning Bayesian Networks from Ordinal Data JMLR 2021
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance NIPS 2021
Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021
High-dimensional Bayesian optimization with sparse axis-aligned subspaces UAI 2021
Hybrid Message Passing With Performance-Driven Structures for Facial Action Unit Detection CVPR 2021
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability NIPS 2021
Non Parametric Graph Learning for Bayesian Graph Neural Networks UAI 2020
Tuning Causal Discovery Algorithms PGM 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
PoRB-Nets: Poisson Process Radial Basis Function Networks UAI 2020