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 1351–1375 of 2226 papers

TitleStatusHype
Analogy as Nonparametric Bayesian Inference over Relational Systems—0
Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics—0
Bayesian Adversarial Human Motion SynthesisCode1
Variational Bayesian Inference for Crowdsourcing Predictions—0
Adaptive quadrature schemes for Bayesian inference via active learning—0
QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision—0
Probabilistic Object Classification using CNN ML-MAP layers—0
VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics—0
Functional Space Variational Inference for Uncertainty Estimation in Computer Aided Diagnosis—0
Model Evidence with Fast Tree Based QuadratureCode0
Is there a wave excitation in the Thalamus?—0
Simulation-Based Inference for Global Health DecisionsCode2
Variational Inference as Iterative Projection in a Bayesian Hilbert Space with Application to Robotic State Estimation—0
On Kalman-Bucy filters, linear quadratic control and active inferenceCode0
Building general Langevin models from discrete data sets—0
Data-Driven Verification under Signal Temporal Logic Constraints—0
Amortized Bayesian Inference for Models of Cognition—0
ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction—0
Bayesian inference of infected patients in group testing with prevalence estimationCode0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
The Two Kinds of Free Energy and the Bayesian RevolutionCode0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck—0
Practical calibration of the temperature parameter in Gibbs posteriorsCode0
Gaussian Process Learning-based Probabilistic Optimal Power Flow—0
Show:102550
← PrevPage 55 of 90Next →

Benchmark Results

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