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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 611–620 of 2226 papers

TitleStatusHype
Distributed Bayesian Inference for Large-Scale IoT Systems—0
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis—0
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear ModelCode0
Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?—0
Bayesian Metaplasticity from Synaptic Uncertainty—0
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive SpaceCode0
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling—0
Vehicle Lane Change Prediction based on Knowledge Graph Embeddings and Bayesian Inference—0
Learning Differentiable Particle Filter on the FlyCode0
nbi: the Astronomer's Package for Neural Posterior Estimation—0
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Benchmark Results

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