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 1611–1620 of 2226 papers

TitleStatusHype
Switching Linear Dynamics for Variational Bayes Filtering—0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over SimplexCode0
Data Augementation with Polya Inverse Gamma—0
Fast and Robust Rank Aggregation against Model MisspecificationCode0
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical SystemsCode0
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionCode0
Walsh-Hadamard Variational Inference for Bayesian Deep Learning—0
Variational Bayes: A report on approaches and applications—0
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models—0
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian InferenceCode0
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Benchmark Results

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