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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
Bayesian Inference in Physics-Driven Problems with Adversarial Priors—0
Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline—0
Bayesian Inference in Physics-Based Nonlinear Flame Models—0
Bayesian Inference in Model-Based Machine Vision—0
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model—0
Approximate Bayesian inference as a gauge theory—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations—0
Bayesian inference in hierarchical models by combining independent posteriors—0
Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs—0
Efficient Debiased Evidence Estimation by Multilevel Monte Carlo Sampling—0
Bayesian Inference in Cumulative Distribution Fields—0
Efficient Bayesian synthetic likelihood with whitening transformations—0
Efficient Bayesian species tree inference under the multi-species coalescent—0
Bayesian inference from time series of allele frequency data using exact simulation techniques—0
Applications of the Free Energy Principle to Machine Learning and Neuroscience—0
Adjoint-aided inference of Gaussian process driven differential equations—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
Accelerating Langevin Sampling with Birth-death—0
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems—0
Bayesian Inference for the Multinomial Probit Model under Gaussian Prior Distribution—0
Efficient Bayesian Inference for Nested Simulators—0
Efficient posterior inference & generalization in physics-based Bayesian inference with conditional GANs—0
Efficient Bayesian Inference for a Gaussian Process Density Model—0
Efficient Reinforcement Learning with Large Language Model Priors—0
Bayesian inference for the mixed conditional heteroskedasticity model—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
A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series—0
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems—0
Efficient Attack Graph Analysis through Approximate Inference—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
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
Bayesian Inference for Structured Spike and Slab Priors—0
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
Efficient acquisition rules for model-based approximate Bayesian computation—0
Bayesian inference for spatio-temporal spike-and-slab priors—0
Dynamics on Lie groups with applications to attitude estimation—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
Bayesian Inference for Radar Imagery Based Surveillance—0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Ensemble Kalman filter for uncertainty in human language comprehension—0
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization—0
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Benchmark Results

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