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Bayesian Inference

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

Papers

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Showing 11–20 of 2226 papers

TitleStatusHype
BayesFlow: Amortized Bayesian Workflows With Neural NetworksCode2
pymdp: A Python library for active inference in discrete state spacesCode2
Scalable Spatiotemporal Prediction with Bayesian Neural FieldsCode2
Simulation-Based Inference for Global Health DecisionsCode2
All-in-one simulation-based inferenceCode2
Bayesian Flow NetworksCode2
Aligning language models with human preferencesCode2
Demonstration of Robust and Efficient Quantum Property Learning with Shallow ShadowsCode2
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and ForecastingCode2
The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparisonCode2
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Benchmark Results

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