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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 1081–1090 of 2226 papers

TitleStatusHype
Goal-Directed Planning by Reinforcement Learning and Active Inference—0
Being a Bit Frequentist Improves Bayesian Neural NetworksCode0
Quasi-Bayesian Dual Instrumental Variable RegressionCode0
Variational Causal Networks: Approximate Bayesian Inference over Causal StructuresCode1
Deep Bayesian Unsupervised Lifelong LearningCode1
Analog Seizure Detection for Implanted Responsive Neurostimulation—0
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs—0
Quantum Speedup of Natural Gradient for Variational Bayes—0
An Interpretable Neural Network for Parameter Inference—0
RNN with Particle Flow for Probabilistic Spatio-temporal ForecastingCode1
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Benchmark Results

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