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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 201–210 of 2226 papers

TitleStatusHype
Deep Bayesian Unsupervised Lifelong LearningCode1
Scalable Random Feature Latent Variable ModelsCode1
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context LearningCode1
Semi-supervised Impedance Inversion by Bayesian Neural Network Based on 2-d CNN Pre-trainingCode1
Diffusive Gibbs SamplingCode1
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive FlowsCode1
Efficient Online Bayesian Inference for Neural BanditsCode1
Gaussian Stochastic Weight Averaging for Bayesian Low-Rank Adaptation of Large Language ModelsCode1
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian NetworksCode1
Variational Item Response Theory: Fast, Accurate, and ExpressiveCode1
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Benchmark Results

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