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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 76–100 of 2226 papers

TitleStatusHype
Bayesian Inference with Latent Hamiltonian Neural NetworksCode1
Amortized Monte Carlo IntegrationCode1
Can Transformers Learn Full Bayesian Inference in Context?Code1
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
Continual Learning via Sequential Function-Space Variational InferenceCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulatorsCode1
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty QuantificationCode1
Dangers of Bayesian Model Averaging under Covariate ShiftCode1
A friendly introduction to triangular transportCode1
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
Neural Clustering ProcessesCode1
Discriminative Training of VBx DiarizationCode1
Accelerated Bayesian SED Modeling using Amortized Neural Posterior EstimationCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Understanding and Accelerating Particle-Based Variational InferenceCode1
A practical tutorial on Variational BayesCode1
Bayesian hierarchical stacking: Some models are (somewhere) usefulCode1
Efficient Online Bayesian Inference for Neural BanditsCode1
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantificationCode1
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
Triple equivalence for the emergence of biological intelligenceCode1
Bayesian neural networks via MCMC: a Python-based tutorialCode1
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Benchmark Results

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