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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 626–650 of 2226 papers

TitleStatusHype
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimationCode0
Digital Twin Framework for Optimal and Autonomous Decision-Making in Cyber-Physical Systems: Enhancing Reliability and Adaptability in the Oil and Gas Industry—0
Beyond the Power Law: Estimation, Goodness-of-Fit, and a Semiparametric Extension in Complex Networks—0
Bayesian mechanics of self-organising systems—0
Bayes in the age of intelligent machines—0
Are Normalizing Flows the Key to Unlocking the Exponential Mechanism?Code0
The Hyperdimensional Transform for Distributional Modelling, Regression and ClassificationCode0
Frequentist Guarantees of Distributed (Non)-Bayesian Inference—0
USLR: an open-source tool for unbiased and smooth longitudinal registration of brain MRCode0
Joint Location Sensing and Channel Estimation for IRS-Aided mmWave ISAC Systems—0
BClean: A Bayesian Data Cleaning SystemCode0
Operational modal analysis of under-determined system based on Bayesian CP decomposition—0
Conditional Optimal Transport on Function SpacesCode0
An Unsupervised Deep Learning Approach for the Wave Equation Inverse Problem—0
Flexible Bayesian Inference on Partially Observed Epidemics—0
Riemannian Laplace Approximation with the Fisher MetricCode0
Robust and Conjugate Gaussian Process RegressionCode0
Projecting basis functions with tensor networks for Gaussian process regression—0
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks—0
Inferring to C or not to C: Evolutionary games with Bayesian inferential strategies—0
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model AccelerationCode0
Bayesian Neural Controlled Differential Equations for Treatment Effect EstimationCode0
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian InferenceCode0
Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN samplerCode0
Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning—0
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Benchmark Results

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