SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1591–1600 of 2226 papers

TitleStatusHype
Switching Linear Dynamics for Variational Bayes Filtering—0
Data Augementation with Polya Inverse Gamma—0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over SimplexCode0
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionCode0
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical SystemsCode0
Walsh-Hadamard Variational Inference for Bayesian Deep Learning—0
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models—0
Variational Bayes: A report on approaches and applications—0
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian InferenceCode0
Decentralized Bayesian Learning over Graphs—0
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Benchmark Results

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