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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 1901–1925 of 2226 papers

TitleStatusHype
Bayesian Inference of Log Determinants—0
Efficient acquisition rules for model-based approximate Bayesian computation—0
Adaptive Gaussian process approximation for Bayesian inference with expensive likelihood functionsCode0
Cohort effects in mortality modelling: a Bayesian state-space approach—0
Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models—0
An embedded segmental K-means model for unsupervised segmentation and clustering of speechCode0
Inference of epidemiological parameters from household stratified data—0
Differentially Private Bayesian Learning on Distributed DataCode0
Signal-based Bayesian Seismic Monitoring—0
The variational Laplace approach to approximate Bayesian inference—0
Bayesian inference on random simple graphs with power law degree distributions—0
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable CouplingsCode0
Linear, Machine Learning and Probabilistic Approaches for Time Series Analysis—0
The Stochastic complexity of spin models: Are pairwise models really simple?—0
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence ClusteringCode0
Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment—0
Bone fusion in normal and pathological development is constrained by the network architecture of the human skull—0
Adversarial Message Passing For Graphical Models—0
Expectation Propagation performs a smoothed gradient descent—0
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo—0
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics—0
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models—0
A Probabilistic Model of Social Decision Making based on Reward Maximization—0
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models—0
Efficient Likelihood Bayesian Constrained Local Model—0
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Benchmark Results

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