SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Showing 326350 of 2226 papers

TitleStatusHype
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-DivergencesCode0
Detecting structural perturbations from time series with deep learningCode0
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systemsCode0
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning AlgorithmsCode0
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in KenyaCode0
On the representation and learning of monotone triangular transport mapsCode0
Deep Neural Networks as Gaussian ProcessesCode0
Differentially Private Bayesian Inference for Exponential FamiliesCode0
Deep Bayesian Structure NetworksCode0
Deep Active Inference as Variational Policy GradientsCode0
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable CouplingsCode0
Deep Bayesian inference for seismic imaging with tasksCode0
Bayesian adaptive and interpretable functional regression for exposure profilesCode0
Debiased Bayesian inference for average treatment effectsCode0
Data Subsampling for Bayesian Neural NetworksCode0
Bayesian Approaches to Shrinkage and Sparse EstimationCode0
PDE-constrained Gaussian process surrogate modeling with uncertain data locationsCode0
Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamicsCode0
Bayesian posterior repartitioning for nested samplingCode0
Learning to infer in recurrent biological networksCode0
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-upCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active InferenceCode0
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma AugmentationCode0
deBInfer: Bayesian inference for dynamical models of biological systems in RCode0
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Benchmark Results

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