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 1431–1440 of 2226 papers

TitleStatusHype
Bayesian task embedding for few-shot Bayesian optimizationCode0
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics—0
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference—0
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning—0
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning AlgorithmsCode0
Attention-Aware Answers of the Crowd—0
Blang: Bayesian declarative modelling of general data structures and inference via algorithms based on distribution continuaCode0
Quantile Propagation for Wasserstein-Approximate Gaussian ProcessesCode0
NFAD: Fixing anomaly detection using normalizing flowsCode0
Normalizing Constant Estimation with Gaussianized Bridge SamplingCode0
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Benchmark Results

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