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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 651–660 of 2226 papers

TitleStatusHype
Robust probabilistic inference via a constrained transport metricCode0
PyVBMC: Efficient Bayesian inference in PythonCode1
Upper Bound of Real Log Canonical Threshold of Tensor Decomposition and its Application to Bayesian Inference—0
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian InferenceCode0
Simulation-based Bayesian inference for robotic grasping—0
Fast post-process Bayesian inference with Variational Sparse Bayesian QuadratureCode0
Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal MetricsCode0
Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering—0
Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamicsCode0
A normative theory of social conflict—0
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Benchmark Results

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