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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 871–880 of 2226 papers

TitleStatusHype
Learning Latent Structural Causal Models—0
Bayesian inference is facilitated by modular neural networks with different time scalesCode0
Efficient identification of informative features in simulation-based inferenceCode0
Bayesian deep learning framework for uncertainty quantification in high dimensions—0
Uncertain Evidence in Probabilistic Models and Stochastic Simulators—0
On Representations of Mean-Field Variational Inference—0
Bottom-up data integration in polymer models of chromatin organisation—0
Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery—0
Variational Model Perturbation for Source-Free Domain AdaptationCode0
Deep Learning Aided Laplace Based Bayesian Inference for Epidemiological Systems—0
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Benchmark Results

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