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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 211–220 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Calibrating Transformers via Sparse Gaussian Processes	Mar 4, 2023	Bayesian InferenceGaussian Processes	CodeCode Available	1	5
TensorBNN: Bayesian Inference for Neural Networks using Tensorflow	Sep 30, 2020	Bayesian InferenceGPU	CodeCode Available	1	5
A Framework for Improving the Reliability of Black-box Variational Inference	Mar 29, 2022	Bayesian InferenceStochastic Optimization	CodeCode Available	1	5
Can Transformers Learn Full Bayesian Inference in Context?	Jan 28, 2025	Bayesian InferenceIn-Context Learning	CodeCode Available	1	5
Too many cooks: Bayesian inference for coordinating multi-agent collaboration	Mar 26, 2020	Bayesian Inference	CodeCode Available	1	5
Torchtree: flexible phylogenetic model development and inference using PyTorch	Jun 26, 2024	Bayesian InferenceVariational Inference	CodeCode Available	1	5
A generative flow for conditional sampling via optimal transport	Jul 9, 2023	Bayesian InferenceDensity Estimation	CodeCode Available	0	5
COVID-19 detection using chest X-rays: is lung segmentation important for generalization?	Apr 12, 2021	Bayesian InferenceGeneral Classification	CodeCode Available	0	5
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data	Dec 3, 2015	Bayesian InferenceCommon Sense Reasoning	CodeCode Available	0	5
A General Framework for Uncertainty Estimation in Deep Learning	Jul 16, 2019	Autonomous DrivingBayesian Inference	CodeCode Available	0	5

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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