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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 1321–1330 of 2226 papers

TitleStatusHype
Kernel Stein Generative Modeling—0
Meta-Learning Divergences of Variational Inference—0
Stochastic Variational Bayesian Inference for a Nonlinear Forward Model—0
The FMRIB Variational Bayesian Inference Tutorial II: Stochastic Variational Bayes—0
WattScale: A Data-driven Approach for Energy Efficiency Analytics of Buildings at Scale—0
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference—0
Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints—0
Bayesian Coresets: Revisiting the Nonconvex Optimization PerspectiveCode1
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo—0
Bayesian Low Rank Tensor Ring Model for Image Completion—0
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Benchmark Results

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