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

Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024

Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024

FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NIPS 2024

Spatial properties of Bayesian unsupervised trees COLT 2024

Information-theoretic Analysis of Bayesian Test Data Sensitivity AISTATS 2024

HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NIPS 2024

Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NIPS 2024

Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference L4DC 2024

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results AISTATS 2024

Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors AISTATS 2024

Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NIPS 2024

Subsampling Error in Stochastic Gradient Langevin Diffusions AISTATS 2024

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models NIPS 2024

Pure Differential Privacy for Functional Summaries with a Laplace-like Process JMLR 2024

BMRS: Bayesian Model Reduction for Structured Pruning NIPS 2024

Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space AAAI 2024

Bayes-optimal learning of an extensive-width neural network from quadratically many samples NIPS 2024

Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators AISTATS 2024

Stochastic Approximation with Biased MCMC for Expectation Maximization AISTATS 2024

Probabilistic size-and-shape functional mixed models NIPS 2024

Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation NIPS 2024

Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations AISTATS 2024

Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism NIPS 2024

Score Operator Newton transport AISTATS 2024

A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators JMLR 2024