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posterior inference

138 papers

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Co-occurring keywords

bayesian inference (1907) variational inference (2069) markov chain monte carlo (725) bayesian nonparametrics (270) gaussian process (1200) uncertainty quantification (1393) gibbs sampling (201) mcmc sampling (70) generative model (2892) importance sampling (318)

Papers

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference ICML 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference ICML 2023
Is Learning Summary Statistics Necessary for Likelihood-free Inference? ICML 2023
Revisiting Structured Variational Autoencoders ICML 2023
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery NIPS 2023
Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images AISTATS 2023
Bayesian Model Averaging of Chain Event Graphs for Robust Explanatory Modelling PGM 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation AISTATS 2022
Foundation Posteriors for Approximate Probabilistic Inference NIPS 2022
Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models JMLR 2022
Learning Tractable Probabilistic Models from Inconsistent Local Estimates NIPS 2022
Tractable Uncertainty for Structure Learning ICML 2022
Probabilistic surrogate networks for simulators with unbounded randomness UAI 2022
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One JMLR 2022
On the detrimental effect of invariances in the likelihood for variational inference NIPS 2022
Particle-Gibbs Sampling for Bayesian Feature Allocation Models JMLR 2021
Bayesian Bellman Operators NIPS 2021
Bayesian time-aligned factor analysis of paired multivariate time series JMLR 2021
Nonparametric Hamiltonian Monte Carlo ICML 2021
Doubly non-central beta matrix factorization for DNA methylation data UAI 2021
Differentially Private Bayesian Inference for Generalized Linear Models ICML 2021
Variational Multi-Task Learning with Gumbel-Softmax Priors NIPS 2021
Improving predictions of Bayesian neural nets via local linearization AISTATS 2021
Leveraging probabilistic circuits for nonparametric multi-output regression UAI 2021