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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 1371–1380 of 2226 papers

TitleStatusHype
Variational Inference with Continuously-Indexed Normalizing FlowsCode0
Meta-Learning Divergences of Variational Inference—0
Kernel Stein Generative Modeling—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
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