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 421–430 of 2226 papers

TitleStatusHype
A hybrid tau-leap for simulating chemical kinetics with applications to parameter estimation—0
Quantifying cell cycle regulation by tissue crowdingCode0
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
Continual Learning via Sequential Function-Space Variational InferenceCode1
Deep de Finetti: Recovering Topic Distributions from Large Language Models—0
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Benchmark Results

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