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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 926–950 of 2226 papers

TitleStatusHype
Learning Summary Statistics for Bayesian Inference with AutoencodersCode0
Simplifying deflation for non-convex optimization with applications in Bayesian inference and topology optimization—0
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method—0
A Kernel Learning Method for Backward SDE Filter—0
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image AnalysisCode0
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning—0
Bayesian inference of spatial and temporal relations in AI patents for EU countries—0
Asymptotic properties of Bayesian inference in linear regression with a structural break—0
Online, Informative MCMC Thinning with Kernelized Stein DiscrepancyCode0
Incorporating Bayesian approaches in Deep Learning Research—0
A visual exploration of Gaussian Processes and Infinite Neural Networks—0
Bayesian sense of time in biological and artificial brains—0
Fully Adaptive Bayesian Algorithm for Data Analysis, FABADACode1
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture ModelsCode0
pymdp: A Python library for active inference in discrete state spacesCode2
Loss-calibrated expectation propagation for approximate Bayesian decision-making—0
SpectraNet: Learned Recognition of Artificial Satellites From High Contrast Spectroscopic Imagery—0
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband ItemsCode0
Classifying Turbulent Environments via Machine Learning—0
Bayesian Invariant Risk Minimization—0
Inferring perceptual decision making parameters from behavior in production and reproduction tasks—0
Interpreting Dynamical Systems as Bayesian Reasoners—0
Reactive Message Passing for Scalable Bayesian InferenceCode1
Bayesian Approaches to Shrinkage and Sparse EstimationCode0
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Benchmark Results

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