SOTAVerified

Bayesian Inference

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

Papers

Showing 110 of 2226 papers

TitleStatusHype
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a SecondCode5
BlackJAX: Composable Bayesian inference in JAXCode5
sbi reloaded: a toolkit for simulation-based inference workflowsCode4
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient FlowsCode2
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and ForecastingCode2
All-in-one simulation-based inferenceCode2
BSD: a Bayesian framework for parametric models of neural spectraCode2
BayesFlow: Amortized Bayesian Workflows With Neural NetworksCode2
Aligning language models with human preferencesCode2
Bayesian Flow NetworksCode2
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Benchmark Results

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