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 601–610 of 2226 papers

TitleStatusHype
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks—0
Stable generative modeling using Schrödinger bridges—0
Neural Population Decoding and Imbalanced Multi-Omic Datasets For Cancer Subtype Diagnosis—0
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration—0
A Compact Representation for Bayesian Neural Networks By Removing Permutation SymmetryCode0
Tractable Function-Space Variational Inference in Bayesian Neural NetworksCode0
Deep de Finetti: Recovering Topic Distributions from Large Language Models—0
Bayesian Analysis of Combinatorial Gaussian Process Bandits—0
Stochastic Control Barrier Functions with Bayesian Inference for Unknown Stochastic Differential Equations—0
Observation-Augmented Contextual Multi-Armed Bandits for Robotic Search and Exploration—0
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Benchmark Results

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