SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 2226 papers

TitleStatusHype
QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative ModelsCode1
Bayesian graph convolutional neural networks via tempered MCMCCode1
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
Bayesian hierarchical stacking: Some models are (somewhere) usefulCode1
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
BayesFlow: Learning complex stochastic models with invertible neural networksCode1
Bayesian Adversarial Human Motion SynthesisCode1
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian InferenceCode1
Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief PropagationCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
BayesianFitForecast: A User-Friendly R Toolbox for Parameter Estimation and Forecasting with Ordinary Differential EquationsCode1
BayesDLL: Bayesian Deep Learning LibraryCode1
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Variational multiple shooting for Bayesian ODEs with Gaussian processesCode1
Bayesian neural networks via MCMC: a Python-based tutorialCode1
Bayesian continual learning and forgetting in neural networksCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
A Primer on Bayesian Neural Networks: Review and DebatesCode1
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
Calibrating Transformers via Sparse Gaussian ProcessesCode1
Complete parameter inference for GW150914 using deep learningCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
Continual Learning via Sequential Function-Space Variational InferenceCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Show:102550
← PrevPage 6 of 90Next →

Benchmark Results

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