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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 1901–1950 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
Adams Conditioning and Likelihood Ratio Transfer Mediated Inference—0
Generalized Dropout—0
The Recycling Gibbs Sampler for Efficient Learning—0
Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference—0
Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures—0
Variational Bayes In Private Settings (VIPS)Code0
Fuzzy Bayesian LearningCode0
Joint Target Detection and Tracking in Multipath Environment: A Variational Bayesian Approach—0
Differentially Private Variational Inference for Non-conjugate ModelsCode1
Operator Variational Inference—0
Bayesian latent structure discovery from multi-neuron recordingsCode0
Recurrent switching linear dynamical systemsCode0
Body movement to sound interface with vector autoregressive hierarchical hidden Markov models—0
Stochastic inference with spiking neurons in the high-conductance state—0
Reparameterization Gradients through Acceptance-Rejection Sampling AlgorithmsCode0
Spatio-temporal Gaussian processes modeling of dynamical systems in systems biology—0
deBInfer: Bayesian inference for dynamical models of biological systems in RCode0
Nonparametric Bayesian inference of the microcanonical stochastic block model—0
Pano2CAD: Room Layout From A Single Panorama Image—0
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy imagesCode1
Semiring Programming: A Declarative Framework for Generalized Sum Product Problems—0
Bayesian Reinforcement Learning: A Survey—0
Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals—0
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning—0
Adaptive matching pursuit for sparse signal recovery—0
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Benchmark Results

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