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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
QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative ModelsCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
Continual Learning via Sequential Function-Space Variational InferenceCode1
Cyclical Stochastic Gradient MCMC for Bayesian Deep LearningCode1
Amortizing intractable inference in large language modelsCode1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Complete parameter inference for GW150914 using deep learningCode1
Calibrating Transformers via Sparse Gaussian ProcessesCode1
Amortized Monte Carlo IntegrationCode1
Can Transformers Learn Full Bayesian Inference in Context?Code1
Antipodes of Label Differential Privacy: PATE and ALIBICode1
Convolutional Bayesian Kernel Inference for 3D Semantic MappingCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
D3p -- A Python Package for Differentially-Private Probabilistic ProgrammingCode1
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
Dangers of Bayesian Model Averaging under Covariate ShiftCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
A practical tutorial on Variational BayesCode1
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy imagesCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Diffusive Gibbs SamplingCode1
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context LearningCode1
A Primer on Bayesian Neural Networks: Review and DebatesCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
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Benchmark Results

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