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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 601–610 of 2226 papers

TitleStatusHype
Federated Variational Inference: Towards Improved Personalization and Generalization—0
Explaining Emergent In-Context Learning as Kernel Regression—0
PDE-constrained Gaussian process surrogate modeling with uncertain data locationsCode0
Massively Parallel Reweighted Wake-Sleep—0
Augmented Message Passing Stein Variational Gradient Descent—0
A Simple Generative Model of Logical Reasoning and Statistical Learning—0
Model-based Validation as Probabilistic InferenceCode0
Score Operator Newton transport—0
Thompson Sampling for Parameterized Markov Decision Processes with Uninformative Actions—0
Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition—0
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Benchmark Results

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