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Bayesian Inference

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

Papers

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Showing 151–175 of 2226 papers

TitleStatusHype
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantificationCode1
Towards constraining warm dark matter with stellar streams through neural simulation-based inferenceCode1
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious timeCode1
Enriching ImageNet with Human Similarity Judgments and Psychological EmbeddingsCode1
Transforming Gaussian Processes With Normalizing FlowsCode1
Bayesian Deep Learning via Subnetwork InferenceCode1
OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in GermanyCode1
TensorBNN: Bayesian Inference for Neural Networks using TensorflowCode1
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient DescentCode1
FedBE: Making Bayesian Model Ensemble Applicable to Federated LearningCode1
Complete parameter inference for GW150914 using deep learningCode1
Lifelong Incremental Reinforcement Learning with Online Bayesian InferenceCode1
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty QuantificationCode1
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian ProcessesCode1
Fast and Accurate Forecasting of COVID-19 Deaths Using the SIkJα ModelCode1
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural NetworksCode1
Bayesian Coresets: Revisiting the Nonconvex Optimization PerspectiveCode1
Multi-marginal optimal transport and probabilistic graphical modelsCode1
Variational Bayesian Monte Carlo with Noisy LikelihoodsCode1
Online Bayesian Goal Inference for Boundedly-Rational Planning AgentsCode1
Probabilistic AutoencoderCode1
Variational Auto-Regressive Gaussian Processes for Continual LearningCode1
Bayesian Adversarial Human Motion SynthesisCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
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Benchmark Results

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