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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 1876–1900 of 2226 papers

TitleStatusHype
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational InferenceCode0
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal PosteriorsCode0
A Compact Representation for Bayesian Neural Networks By Removing Permutation SymmetryCode0
Challenges in Markov chain Monte Carlo for Bayesian neural networksCode0
Variational methods for simulation-based inferenceCode0
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimationCode0
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic netCode0
Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocationCode0
Estimating Idea Production: A Methodological SurveyCode0
A Metaheuristic for Amortized Search in High-Dimensional Parameter SpacesCode0
Estimating Risk and Uncertainty in Deep Reinforcement LearningCode0
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware PriorsCode0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at ScaleCode0
Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI CapabilitiesCode0
Variational Bayes In Private Settings (VIPS)Code0
Evaluating Topic Quality with Posterior VariabilityCode0
Mismatched Estimation of rank-one symmetric matrices under Gaussian noiseCode0
Recurrent switching linear dynamical systemsCode0
Mixed Variational InferenceCode0
Batch Bayesian Optimization via Particle Gradient FlowsCode0
Calibrating Neural Simulation-Based Inference with Differentiable Coverage ProbabilityCode0
Bayesian latent structure discovery from multi-neuron recordingsCode0
Bayesian Inference of Minimally Complex Models with Interactions of Arbitrary OrderCode0
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive SpaceCode0
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Benchmark Results

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