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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 851–900 of 2226 papers

TitleStatusHype
Dynamics on Lie groups with applications to attitude estimation—0
Exploration in Interactive Personalized Music Recommendation: A Reinforcement Learning Approach—0
Efficient acquisition rules for model-based approximate Bayesian computation—0
Bayesian inference for spatio-temporal spike-and-slab priors—0
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
Efficient Attack Graph Analysis through Approximate Inference—0
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems—0
Efficient Bayesian Inference for a Gaussian Process Density Model—0
Efficient Bayesian Inference for Nested Simulators—0
Bayesian Inference for the Multinomial Probit Model under Gaussian Prior Distribution—0
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems—0
Efficient Bayesian species tree inference under the multi-species coalescent—0
Efficient Bayesian synthetic likelihood with whitening transformations—0
Efficient Debiased Evidence Estimation by Multilevel Monte Carlo Sampling—0
Bayesian Inference in Cumulative Distribution Fields—0
Bayesian inference in hierarchical models by combining independent posteriors—0
Efficient Likelihood Bayesian Constrained Local Model—0
Efficient Low-Order Approximation of First-Passage Time Distributions—0
Efficient MCMC Sampling with Expensive-to-Compute and Irregular Likelihoods—0
Efficient Membership Inference Attacks by Bayesian Neural Network—0
Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory—0
Bayesian Inference in Model-Based Machine Vision—0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline—0
Efficient posterior inference & generalization in physics-based Bayesian inference with conditional GANs—0
Bayesian Inference in Physics-Driven Problems with Adversarial Priors—0
Efficient Reinforcement Learning with Large Language Model Priors—0
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Efficient transfer learning and online adaptation with latent variable models for continuous control—0
Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning—0
EinSteinVI: General and Integrated Stein Variational Inference—0
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale—0
Accelerating MCMC via Parallel Predictive Prefetching—0
Bayesian inference of a new Mallows model for characterising symptom sequences applied in primary progressive aphasia—0
Elements of Sequential Monte Carlo—0
Eliciting Language Model Behaviors with Investigator Agents—0
Embarrassingly parallel MCMC using deep invertible transformations—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models—0
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization—0
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
EMHMM Simulation Study—0
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows—0
Enhanced gradient-based MCMC in discrete spaces—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Bayesian Inference of Log Determinants—0
Ensemble Kalman filter for uncertainty in human language comprehension—0
A Tractable Fully Bayesian Method for the Stochastic Block Model—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified