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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 151–200 of 2226 papers

TitleStatusHype
FLORA: Formal Language Model Enables Robust Training-free Zero-shot Object Referring Analysis—0
Tutorial: VAE as an inference paradigm for neuroimaging—0
Distilling Calibration via Conformalized Credal Inference—0
Comparing latent inequality with ordinal data—0
Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse ProblemsCode2
A Bayesian Approach for Discovering Time- Delayed Differential Equation from Data—0
Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals—0
Generative Emergent Communication: Large Language Model is a Collective World Model—0
Testing and Improving the Robustness of Amortized Bayesian Inference for Cognitive ModelsCode0
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network—0
Exploiting Dynamic Sparsity for Near-Field Spatial Non-Stationary XL-MIMO Channel Tracking—0
Variational Bayesian Inference for Tensor Robust Principal Component Analysis—0
Generative Modeling: A Review—0
Transport Quasi-Monte Carlo—0
Stochastic Model of siRNA Endosomal Escape Mediated by Fusogenic Peptides in OVCAR-3Code0
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles—0
Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control—0
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference—0
Relational Neurosymbolic Markov Models—0
Improving Cooperation in Language Games with Bayesian Inference and the Cognitive HierarchyCode0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Information-Geometric Barycenters for Bayesian Federated Learning—0
Bayesian inference of mean velocity fields and turbulence models from flow MRI—0
Adaptive Nonparametric Perturbations of Parametric Bayesian ModelsCode0
BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation—0
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