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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 51–60 of 2226 papers

Title	Date	Tasks	Status	Hype
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective	Dec 4, 2023	Bayesian Inference	CodeCode Available	1
The Transient Nature of Emergent In-Context Learning in Transformers	Nov 14, 2023	Bayesian InferenceIn-Context Learning	CodeCode Available	1
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting	Nov 3, 2023	Bayesian InferenceTime Series	CodeCode Available	1
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference	Oct 17, 2023	Bayesian InferenceImage Generation	CodeCode Available	1
Amortizing intractable inference in large language models	Oct 6, 2023	Bayesian InferenceDiversity	CodeCode Available	1
Discriminative Training of VBx Diarization	Oct 4, 2023	Bayesian Inference	CodeCode Available	1
A Primer on Bayesian Neural Networks: Review and Debates	Sep 28, 2023	Bayesian Inference	CodeCode Available	1
BayesDLL: Bayesian Deep Learning Library	Sep 22, 2023	Bayesian InferenceDeep Learning	CodeCode Available	1
Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning	Sep 12, 2023	Bayesian Inference	CodeCode Available	1
Monte Carlo guided Diffusion for Bayesian linear inverse problems	Aug 15, 2023	Bayesian Inference	CodeCode Available	1

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	F-SWA	Accuracy	83.61	—	Unverified
2	F-SWAG	Accuracy	80.93	—	Unverified