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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 651–675 of 2226 papers

TitleStatusHype
Device Detection and Channel Estimation in MTC with Correlated Activity Pattern—0
Calibrating Neural Simulation-Based Inference with Differentiable Coverage ProbabilityCode0
Sequential Gibbs Posteriors with Applications to Principal Component Analysis—0
Fine-Tuning Generative Models as an Inference Method for Robotic TasksCode0
Simulation-based Bayesian Inference from Privacy Protected DataCode0
Bayesian Flow Networks in Continual Learning—0
Sensitivity-Aware Amortized Bayesian InferenceCode0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
Hierarchical MTC User Activity Detection and Channel Estimation with Unknown Spatial Covariance—0
Worst-Case Analysis is Maximum-A-Posteriori Estimation—0
A Stochastic Particle Variational Bayesian Inference Inspired Deep-Unfolding Network for Non-Convex Parameter Estimation—0
A time-varying finance-led model for U.S. business cycles—0
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian InferenceCode0
Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs—0
Variational Inference for GARCH-family Models—0
Probabilistic Block Term Decomposition for the Modelling of Higher-Order Arrays—0
STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent—0
Towards a Unified Framework for Sequential Decision Making—0
Statistical physics, Bayesian inference and neural information processing—0
A Metaheuristic for Amortized Search in High-Dimensional Parameter SpacesCode0
A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression—0
Entropic Matching for Expectation Propagation of Markov Jump Processes—0
A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth—0
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian ProcessesCode0
Bounded rationality in structured density estimation—0
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Benchmark Results

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