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Bayesian Inference

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 2226 papers

TitleStatusHype
Prediction of Occluded Pedestrians in Road Scenes using Human-like Reasoning: Insights from the OccluRoads Dataset—0
Hardware implementation of timely reliable Bayesian decision-making using memristors—0
DPGIIL: Dirichlet Process-Deep Generative Model-Integrated Incremental Learning for Clustering in Transmissibility-based Online Structural Anomaly Detection—0
The Polynomial Stein Discrepancy for Assessing Moment ConvergenceCode0
Semiparametric Bayesian Difference-in-Differences—0
Path-Guided Particle-based SamplingCode0
MACAW: A Causal Generative Model for Medical ImagingCode0
Physics-informed Gaussian Processes as Linear Model Predictive Controller—0
Extension of compressive sampling to binary vector recovery for model-based defect imaging—0
Investigating Plausibility of Biologically Inspired Bayesian Learning in ANNs—0
ESS-ReduNet: Enhancing Subspace Separability of ReduNet via Dynamic Expansion with Bayesian Inference—0
Belief patterns with information processing—0
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive ModellingCode0
sbi reloaded: a toolkit for simulation-based inference workflowsCode4
Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Connections between sequential Bayesian inference and evolutionary dynamics—0
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation—0
Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow NetworksCode2
Spatial-variant causal Bayesian inference for rapid seismic ground failures and impacts estimation—0
Variational Bayesian Bow tie Neural Networks with ShrinkageCode0
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data—0
Modeling human decomposition: a Bayesian approach—0
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps—0
Streaming Bayes GFlowNets—0
BayesianFitForecast: A User-Friendly R Toolbox for Parameter Estimation and Forecasting with Ordinary Differential EquationsCode1
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Benchmark Results

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