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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 126–150 of 2226 papers

TitleStatusHype
RNN with Particle Flow for Probabilistic Spatio-temporal ForecastingCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
Antipodes of Label Differential Privacy: PATE and ALIBICode1
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlasCode1
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical ImagingCode1
Bayesian graph convolutional neural networks via tempered MCMCCode1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Learning by example: fast reliability-aware seismic imaging with normalizing flowsCode1
D3p -- A Python Package for Differentially-Private Probabilistic ProgrammingCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
Modeling tail risks of inflation using unobserved component quantile regressionsCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
A practical tutorial on Variational BayesCode1
Trumpets: Injective Flows for Inference and Inverse ProblemsCode1
Scalable Bayesian Inverse Reinforcement LearningCode1
Variational Inference for Deblending Crowded StarfieldsCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
Bayesian hierarchical stacking: Some models are (somewhere) usefulCode1
Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro DataCode1
Towards fast machine-learning-assisted Bayesian posterior inference of microseismic event location and source mechanismCode1
Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational InferenceCode1
Score Matched Neural Exponential Families for Likelihood-Free InferenceCode1
Spacecraft Collision Risk Assessment with Probabilistic ProgrammingCode1
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Benchmark Results

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