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 1401–1425 of 2226 papers

TitleStatusHype
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
Variational Inference as Iterative Projection in a Bayesian Hilbert Space with Application to Robotic State Estimation—0
Building general Langevin models from discrete data sets—0
On Kalman-Bucy filters, linear quadratic control and active inferenceCode0
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
Bayesian Consensus: Consensus Estimates from Miscalibrated Instruments under Heteroscedastic Noise—0
Scaling Bayesian inference of mixed multinomial logit models to very large datasets—0
Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring—0
Active recursive Bayesian inference using Rényi information measures—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
The equivalence between Stein variational gradient descent and black-box variational inference—0
Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market—0
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Benchmark Results

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