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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 1281–1290 of 2226 papers

TitleStatusHype
Lévy walks derived from a Bayesian decision-making model in non-stationary environments—0
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interactionCode0
Bayesian Neural Ordinary Differential Equations—0
Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian InferenceCode0
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent—0
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty RegularizationCode0
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks—0
Generalised Bayesian Filtering via Sequential Monte Carlo—0
Bidirectional Convolutional Poisson Gamma Dynamical SystemsCode0
Baxter Permutation ProcessCode0
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Benchmark Results

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