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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 2001–2025 of 2226 papers

TitleStatusHype
Fully Bayesian inference for latent variable Gaussian process modelsCode0
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian ProcessesCode0
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methodsCode0
Functional Ensemble DistillationCode0
Functional Regularisation for Continual Learning with Gaussian ProcessesCode0
Robustness Guarantees for Bayesian Inference with Gaussian ProcessesCode0
Stochastic Gradient MCMC with Repulsive ForcesCode0
Functional Variational Bayesian Neural NetworksCode0
Robust One Round Federated Learning with Predictive Space Bayesian InferenceCode0
Bayesian Inference on Brain-Computer Interfaces via GLASSCode0
Robust Optimisation Monte CarloCode0
Neural Tangents: Fast and Easy Infinite Neural Networks in PythonCode0
Bayesian inference of species trees using diffusion modelsCode0
Fuzzy Bayesian LearningCode0
Bayesian task embedding for few-shot Bayesian optimizationCode0
Attentional Prototype Inference for Few-Shot SegmentationCode0
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Robust probabilistic inference via a constrained transport metricCode0
Neuron's Eye View: Inferring Features of Complex Stimuli from Neural ResponsesCode0
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse ProblemsCode0
Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphsCode0
Bayesian score calibration for approximate modelsCode0
A Bayesian Monte Carlo approach for predicting the spread of infectious diseasesCode0
Bayesian Robust Aggregation for Federated LearningCode0
Rule-based Bayesian regressionCode0
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Benchmark Results

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