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 1151–1175 of 2226 papers

TitleStatusHype
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters—0
Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference—0
Recent advances in deep learning theory—0
Recent methods from statistical inference and machine learning to improve integrative modeling of macromolecular assemblies—0
Recent Progress in Image Deblurring—0
Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively—0
Reconstructing networks with unknown and heterogeneous errors—0
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference—0
Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior—0
Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo—0
Recursive Metropolis-Hastings Naming Game: Symbol Emergence in a Multi-agent System based on Probabilistic Generative Models—0
Reducing the False Positive Rate Using Bayesian Inference in Autonomous Driving Perception—0
Refining the variational posterior through iterative optimization—0
Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market—0
Regularization by denoising: Bayesian model and Langevin-within-split Gibbs sampling—0
Reinforcement Learning Enhanced PicHunter for Interactive Search—0
Relational Neurosymbolic Markov Models—0
Relative Probability on Finite Outcome Spaces: A Systematic Examination of its Axiomatization, Properties, and Applications—0
Relevance Singular Vector Machine for low-rank matrix sensing—0
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks—0
Reliable ABC model choice via random forests—0
Remarks on kernel Bayes' rule—0
Remote sensing image fusion based on Bayesian GAN—0
Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics—0
Reparameterization invariance in approximate Bayesian inference—0
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Benchmark Results

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