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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 241–250 of 2226 papers

TitleStatusHype
Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning—0
TapType: Ten-finger text entry on everyday surfaces via Bayesian inference—0
Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data—0
Improving Generalization with Flat Hilbert Bayesian Inference—0
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network ApproachCode0
The Benefit of Being Bayesian in Online Conformal PredictionCode0
An uncertainty-aware Digital Shadow for underground multimodal CO2 storage monitoring—0
Thermodynamic Bayesian Inference—0
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active InferenceCode0
Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions—0
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Benchmark Results

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