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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 1026–1050 of 2226 papers

TitleStatusHype
Distributed Variational Bayesian Algorithms Over Sensor Networks—0
A Novel Gaussian Process Based Ground Segmentation Algorithm with Local-Smoothness Estimation—0
A deep learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generation—0
Accelerating a hybrid continuum-atomistic fluidic model with on-the-fly machine learning—0
Distributed Bayesian Inference for Large-Scale IoT Systems—0
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks—0
Bayesian inference for bivariate ranks—0
Bayesian Inference by Symbolic Model Checking—0
Distilling Calibration via Conformalized Credal Inference—0
Bayesian inference as iterated random functions with applications to sequential inference in graphical models—0
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting—0
Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things—0
A normative theory of social conflict—0
A Deep Learning Approach to Dst Index Prediction—0
Discriminative Relational Topic Models—0
Bayesian inference and superstatistics to describe long memory processes of financial time series—0
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation—0
Bayesian inference and role of astrocytes in amyloid-beta dynamics with modelling of Alzheimer's disease using clinical data—0
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics—0
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits—0
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle—0
Dimension reduction via score ratio matching—0
Bayesian inference and neural estimation of acoustic wave propagation—0
A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
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Benchmark Results

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