SOTAVerified

Bayesian Inference

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

Papers

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Showing 1101–1125 of 2226 papers

TitleStatusHype
Bayesian Inference for Gamma Models—0
Separated-Spectral-Distribution Estimation Based on Bayesian Inference with Single RGB Camera—0
Online Bayesian inference for multiple changepoints and risk assessment—0
Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing—0
Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC—0
Calibration and Uncertainty Quantification of Bayesian Convolutional Neural Networks for Geophysical Applications—0
Trajectory Modeling via Random Utility Inverse Reinforcement Learning—0
How particular is the physics of the free energy principle?—0
Vector autoregression models with skewness and heavy tails—0
Metropolis-CVAE: Bootstrapping Labels for Bayesian Inference via Semi-Supervised Conditional Variational Autoencoders—0
Sampling with Trusthworthy Constraints: A Variational Gradient FrameworkCode0
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression—0
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue—0
Privacy Amplification Via Bernoulli Sampling—0
Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics—0
Improved Neuronal Ensemble Inference with Generative Model and MCMC—0
Nonlinear Hawkes Process with Gaussian Process Self Effects—0
Parametrization invariant interpretation of priors and posteriors—0
Bayesian reconstruction of memories stored in neural networks from their connectivityCode0
Attentional Prototype Inference for Few-Shot SegmentationCode0
Priors in Bayesian Deep Learning: A Review—0
High-Performance FPGA-based Accelerator for Bayesian Neural Networks—0
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference—0
Bayesian inference and superstatistics to describe long memory processes of financial time series—0
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Benchmark Results

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