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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 26–50 of 2226 papers

TitleStatusHype
Multilevel neural simulation-based inferenceCode0
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity—0
UAV-Based Remote Sensing of Soil Moisture Across Diverse Land Covers: Validation and Bayesian Uncertainty Characterization—0
Amortized variational transdimensional inferenceCode0
Variational Inference for Latent Variable Models in High Dimensions—0
A Group-Wise Narrow Beam Design for Uplink Channel Estimation in Hybrid Beamforming Systems—0
Joint Activity Detection and Channel Estimation for Massive Connectivity: Where Message Passing Meets Score-Based Generative Priors—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
Model Informed Flows for Bayesian Inference of Probabilistic Programs—0
Position: The Future of Bayesian Prediction Is Prior-Fitted—0
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs—0
Weakly-supervised Localization of Manipulated Image Regions Using Multi-resolution Learned Features—0
Judging LLMs on a Simplex—0
TabPFN: One Model to Rule Them All?Code0
Bayesian Deep Learning for Discrete Choice—0
Generalized Power Priors for Improved Bayesian Inference with Historical Data—0
Inter-Subject Variance Transfer Learning for EMG Pattern Classification Based on Bayesian Inference—0
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation—0
Compositional amortized inference for large-scale hierarchical Bayesian models—0
Understanding Task Representations in Neural Networks via Bayesian Ablation—0
SNAPE-PM: Building and Utilizing Dynamic Partner Models for Adaptive Explanation GenerationCode0
Variational Bayesian Inference for Time-Varying Massive MIMO Channels: Estimation and Detection—0
Efficient MCMC Sampling with Expensive-to-Compute and Irregular Likelihoods—0
Uncertainty-Aware Surrogate-based Amortized Bayesian Inference for Computationally Expensive Models—0
Bayesian Estimation of Causal Effects Using Proxies of a Latent Interference NetworkCode0
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Benchmark Results

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