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 441–450 of 2226 papers

TitleStatusHype
Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief PropagationCode1
Bayesian Metaplasticity from Synaptic Uncertainty—0
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling—0
Vehicle Lane Change Prediction based on Knowledge Graph Embeddings and Bayesian Inference—0
Learning Differentiable Particle Filter on the FlyCode0
Uncertainty Quantification and Propagation in Surrogate-based Bayesian InferenceCode1
nbi: the Astronomer's Package for Neural Posterior Estimation—0
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian PerspectiveCode1
Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal LayersCode0
Bayesian causal discovery from unknown general interventionsCode0
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Benchmark Results

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