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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 701–725 of 2226 papers

TitleStatusHype
Gradient-Based Markov Chain Monte Carlo for MIMO Detection—0
A Review of Change of Variable Formulas for Generative Modeling—0
Pruning a neural network using Bayesian inference—0
Learning from Topology: Cosmological Parameter Estimation from the Large-scale Structure—0
The Bayesian Context Trees State Space Model for time series modelling and forecasting—0
Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood EstimationCode0
A digital twin framework for civil engineering structuresCode0
A theory of data variability in Neural Network Bayesian inference—0
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization ProblemsCode0
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty—0
Amortized Variational Inference: When and Why?Code0
A Bayesian Programming Approach to Car-following Model Calibration and Validation using Limited Data—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Flexible and efficient emulation of spatial extremes processes via variational autoencodersCode0
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout—0
Variational Prediction—0
Bayesian taut splines for estimating the number of modes—0
A generative flow for conditional sampling via optimal transportCode0
Incentive-Theoretic Bayesian Inference for Collaborative Science—0
Uncertainty Informed Optimal Resource Allocation with Gaussian Process based Bayesian Inference—0
Representation Learning via Variational Bayesian Networks—0
Latent SDEs on Homogeneous SpacesCode0
Predictive Coding beyond Correlations—0
Bayesian inference and role of astrocytes in amyloid-beta dynamics with modelling of Alzheimer's disease using clinical data—0
A Hierarchical Bayesian Model for Deep Few-Shot Meta LearningCode0
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Benchmark Results

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