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 711–720 of 2226 papers

TitleStatusHype
Correntropy-Based Improper Likelihood Model for Robust Electrophysiological Source Imaging—0
Cortical Microcircuits from a Generative Vision Model—0
A Tutorial on Sparse Gaussian Processes and Variational Inference—0
Alternating linear scheme in a Bayesian framework for low-rank tensor approximation—0
Adaptive Gaussian process surrogates for Bayesian inference—0
Dynamic Calibration of Nonlinear Sensors with Time-Drifts and Delays by Bayesian Inference—0
Cross-modal Variational Auto-encoder with Distributed Latent Spaces and Associators—0
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference—0
BIBI: Bayesian Inference of Breed Composition—0
Bias or Optimality? Disentangling Bayesian Inference and Learning Biases in Human Decision-Making—0
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Benchmark Results

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