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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 1471–1480 of 2226 papers

TitleStatusHype
Neural Tangents: Fast and Easy Infinite Neural Networks in PythonCode0
Overcoming Catastrophic Forgetting by Generative Regularization—0
A Bayesian Inference Framework for Procedural Material Parameter Estimation—0
On the geometry of Stein variational gradient descent—0
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon SynapseCode0
Mutually Regressive Point ProcessesCode0
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High DimensionsCode0
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models—0
AGEM: Solving Linear Inverse Problems via Deep Priors and SamplingCode0
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
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Benchmark Results

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