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bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

SEL-BALD: Deep Bayesian Active Learning with Selective Labels NIPS 2024
Exploration of the Search Space of Gaussian Graphical Models for Paired Data JMLR 2024
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization JMLR 2024
Virtual-Event-Based Posterior Sampling and Inference for Neyman-Scott Processes JMLR 2024
Tensor-train methods for sequential state and parameter learning in state-space models JMLR 2024
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC JMLR 2024
Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations AISTATS 2024
A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis AAAI 2024
Pure Differential Privacy for Functional Summaries with a Laplace-like Process JMLR 2024
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024
Modeling Random Networks with Heterogeneous Reciprocity JMLR 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024
Differentially private methods for managing model uncertainty in linear regression JMLR 2024
A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators JMLR 2024
Stable Implementation of Probabilistic ODE Solvers JMLR 2024
MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees AAAI 2024
Bayesian Calibration of Win Rate Estimation with LLM Evaluators EMNLP 2024
Data-Driven Knowledge-Aware Inference of Private Information in Continuous Double Auctions AAAI 2024
Subsampling Error in Stochastic Gradient Langevin Diffusions AISTATS 2024
Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024
Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST) JMLR 2024
autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024
Fortuna: A Library for Uncertainty Quantification in Deep Learning JMLR 2024
Gated Inference Network: Inference and Learning State-Space Models NIPS 2024