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Notebooks about Bayesian methods for machine learning
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Notebooks about Bayesian methods for machine learning
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Bayesian Deep Learning: A Survey
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Bayesian modeling with PyMC 5: priors, likelihood, NUTS/ADVI sampling, diagnostics (R-hat, ESS), LOO/WAIC comparison, prediction. Hierarchical, logistic, GP variants; pr…
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Mapping spatiotemporal patterns in an online and continuous fashion
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A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
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Bayesian Optimization as a Coverage Tool for Evaluating LLMs. Accurate evaluation (benchmarking) that's 10 times faster with just a few lines of modular code.
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Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
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"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
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Time-to-event modeling with scikit-survival: Cox PH (elastic net), Random Survival Forests, Boosting, SVMs for censored data. C-index, Brier, time-dependent AUC; Kaplan-…
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Guided statistical analysis: test choice, assumption checks, effect sizes, power, APA reporting. Pick tests, verify assumptions, or format results for publicati