SOTAVerified

Bayesian Inference

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

Papers

Showing 14911500 of 2226 papers

TitleStatusHype
Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage0
Exchangeable Variational Autoencoders with Applications to Genomic Data0
AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithmsCode0
Challenges in Markov chain Monte Carlo for Bayesian neural networksCode0
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition0
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte CarloCode1
Variational Tracking and Prediction with Generative Disentangled State-Space Models0
Bayesian Meta-Learning for the Few-Shot Setting via Deep KernelsCode1
Validated Variational Inference via Practical Posterior Error BoundsCode1
Distilling Importance Sampling for Likelihood Free InferenceCode0
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Benchmark Results

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