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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 461–470 of 2226 papers

TitleStatusHype
Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline—0
Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory—0
Localized Schrödinger Bridge Sampler—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
Half-VAE: An Encoder-Free VAE to Bypass Explicit Inverse Mapping—0
Absolute Ranking: An Essential Normalization for Benchmarking Optimization Algorithms—0
Amortized Bayesian Workflow (Extended Abstract)—0
Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Inverse decision-making using neural amortized Bayesian actorsCode0
Stein transport for Bayesian inference—0
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Benchmark Results

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