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‎notebooks/generalized_linear_models/GLM-hierarchical-jax.ipynb renamed to ‎notebooks/samplers/GLM-hierarchical-jax.ipynb

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‎notebooks/simulation_based_inference/SMC-ABC_Lotka-Volterra_example.ipynb renamed to ‎notebooks/samplers/SMC-ABC_Lotka-Volterra_example.ipynb

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‎notebooks/simulation_based_inference/SMC2_gaussians.ipynb renamed to ‎notebooks/samplers/SMC2_gaussians.ipynb

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‎notebooks/simulation_based_inference/smc.png renamed to ‎notebooks/samplers/smc.png

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‎notebooks/table_of_contents_examples.js

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Gallery.contents = {
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"BEST": "Case Studies",
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"LKJ": "Case Studies",
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"stochastic_volatility": "Case Studies",
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"rugby_analytics": "Case Studies",
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"multilevel_modeling": "Case Studies",
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"putting_workflow": "Case Studies",
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"Diagnosing_biased_Inference_with_Divergences": "Diagnostics and Model Criticism",
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"model_comparison": "Diagnostics and Model Criticism",
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"posterior_predictive": "Diagnostics and Model Criticism",
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"Bayes_factor": "Diagnostics and Model Criticism",
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"GLM": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-linear": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-logistic": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-hierarchical-binominal-model": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-hierarchical": "(Generalized) Linear and Hierarchical Linear Models",
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"hierarchical_partial_pooling": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-model-selection": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-negative-binomial-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-poisson-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-robust-with-outlier-detection": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-robust": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-rolling-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"GLM-hierarchical-advi-minibatch": "(Generalized) Linear and Hierarchical Linear Models",
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"GP-Kron": "Gaussian Processes",
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"GP-Latent": "Gaussian Processes",
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"GP-Marginal": "Gaussian Processes",
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"GP-MaunaLoa": "Gaussian Processes",
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"GP-MaunaLoa2": "Gaussian Processes",
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"GP-MeansAndCovs": "Gaussian Processes",
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"GP-SparseApprox": "Gaussian Processes",
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"GP-TProcess": "Gaussian Processes",
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"GP-smoothing": "Gaussian Processes",
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"gaussian_process": "Gaussian Processes",
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"conditional-autoregressive-model": "Gaussian Processes",
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"log-gaussian-cox-process":"Gaussian Processes",
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"GP-Circular": "Gaussian Processes",
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"dependent_density_regression": "Mixture Models",
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"dp_mix": "Mixture Models",
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"gaussian-mixture-model-advi": "Mixture Models",
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"gaussian_mixture_model": "Mixture Models",
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"case_studies/BEST": "Case Studies",
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"case_studies/LKJ": "Case Studies",
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"case_studies/stochastic_volatility": "Case Studies",
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"case_studies/rugby_analytics": "Case Studies",
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"case_studies/multilevel_modeling": "Case Studies",
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"case_studies/putting_workflow": "Case Studies",
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"diagnostics_and_criticism/Diagnosing_biased_Inference_with_Divergences": "Diagnostics and Model Criticism",
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"diagnostics_and_criticism/model_comparison": "Diagnostics and Model Criticism",
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"diagnostics_and_criticism/posterior_predictive": "Diagnostics and Model Criticism",
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"diagnostics_and_criticism/Bayes_factor": "Diagnostics and Model Criticism",
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"generalized_linear_models/GLM": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-linear": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-logistic": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-hierarchical-binominal-model": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-hierarchical": "(Generalized) Linear and Hierarchical Linear Models",
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"case/studies/hierarchical_partial_pooling": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-model-selection": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-negative-binomial-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-poisson-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-robust-with-outlier-detection": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-robust": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-rolling-regression": "(Generalized) Linear and Hierarchical Linear Models",
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"generalized_linear_models/GLM-hierarchical-advi-minibatch": "(Generalized) Linear and Hierarchical Linear Models",
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"gaussian_processes/GP-Kron": "Gaussian Processes",
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"gaussian_processes/GP-Latent": "Gaussian Processes",
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"gaussian_processes/GP-Marginal": "Gaussian Processes",
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"gaussian_processes/GP-MaunaLoa": "Gaussian Processes",
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"gaussian_processes/GP-MaunaLoa2": "Gaussian Processes",
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"gaussian_processes/GP-MeansAndCovs": "Gaussian Processes",
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"gaussian_processes/GP-SparseApprox": "Gaussian Processes",
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"gaussian_processes/GP-TProcess": "Gaussian Processes",
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"gaussian_processes/GP-smoothing": "Gaussian Processes",
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"gaussian_processes/gaussian_process": "Gaussian Processes",
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"case_studies/conditional-autoregressive-model": "Gaussian Processes",
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"case_studies/log-gaussian-cox-process":"Gaussian Processes",
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"gaussian_processes/GP-Circular": "Gaussian Processes",
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"mixture_models/dependent_density_regression": "Mixture Models",
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"mixture_models/dp_mix": "Mixture Models",
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"variational_inference/gaussian-mixture-model-advi": "Mixture Models",
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"mixture_models/gaussian_mixture_model": "Mixture Models",
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"marginalized_gaussian_mixture_model": "Mixture Models",
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"SMC2_gaussians": "Simulation-based Inference",
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"SMC-ABC_Lotka-Volterra_example": "Simulation-based Inference",
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"bayes_param_survival_pymc3": "Survival Analysis",
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"censored_data": "Survival Analysis",
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"survival_analysis": "Survival Analysis",
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"weibull_aft": "Survival Analysis",
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"cox_model": "Survival Analysis",
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"MvGaussianRandomWalk_demo": "Time Series",
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"AR": "Time Series",
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"Euler-Maruyama_and_SDEs": "Time Series",
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"bayesian_neural_network_advi": "Variational Inference",
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"convolutional_vae_keras_advi": "Variational Inference",
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"empirical-approx-overview": "Variational Inference",
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"lda-advi-aevb": "Variational Inference",
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"normalizing_flows_overview": "Variational Inference",
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"gaussian-mixture-model-advi": "Variational Inference",
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"GLM-hierarchical-advi-minibatch": "Variational Inference",
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"ODE_with_manual_gradients": "Inference in ODE models",
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"ODE_API_introduction": "Inference in ODE models",
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"probabilistic_matrix_factorization": "Case Studies",
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"sampling_conjugate_step":"MCMC",
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"MLDA_introduction": "MCMC",
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"MLDA_simple_linear_regression": "MCMC",
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"MLDA_gravity_surveying": "MCMC",
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"MLDA_variance_reduction_linear_regression": "MCMC",
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"GLM-hierarchical-jax": "MCMC"
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"samplers/SMC2_gaussians": "Simulation-based Inference",
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"samplers/SMC-ABC_Lotka-Volterra_example": "Simulation-based Inference",
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"survival_analysis/bayes_param_survival_pymc3": "Survival Analysis",
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"survival_analysis/censored_data": "Survival Analysis",
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"survival_analysis/survival_analysis": "Survival Analysis",
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"survival_analysis/weibull_aft": "Survival Analysis",
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"survival_analysis/cox_model": "Survival Analysis",
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"time_series/MvGaussianRandomWalk_demo": "Time Series",
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"time_series/R": "Time Series",
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"time_series/Euler-Maruyama_and_SDEs": "Time Series",
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"variational_inference/bayesian_neural_network_advi": "Variational Inference",
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"variational_inference/convolutional_vae_keras_advi": "Variational Inference",
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"variational_inference/empirical-approx-overview": "Variational Inference",
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"variational_inference/lda-advi-aevb": "Variational Inference",
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"variational_inference/normalizing_flows_overview": "Variational Inference",
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"variational_inference/gaussian-mixture-model-advi": "Variational Inference",
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"variational_inference/GLM-hierarchical-advi-minibatch": "Variational Inference",
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"ode_models/ODE_with_manual_gradients": "Inference in ODE models",
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"ode_models/ODE_API_introduction": "Inference in ODE models",
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"case_studies/probabilistic_matrix_factorization": "Case Studies",
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"pymc3_howto/sampling_conjugate_step":"MCMC",
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"samplers/MLDA_introduction": "MCMC",
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"samplers/MLDA_simple_linear_regression": "MCMC",
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"samplers/MLDA_gravity_surveying": "MCMC",
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"samplers/MLDA_variance_reduction_linear_regression": "MCMC",
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"samplers/GLM-hierarchical-jax": "MCMC"
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}

‎notebooks/table_of_contents_tutorials.js

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Gallery.contents = {
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"api_quickstart": "Basics",
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"variational_api_quickstart": "Basics",
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"pymc3_howto/api_quickstart": "Basics",
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"variational_inference/variational_api_quickstart": "Basics",
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"PyMC3_and_Theano.rst": "Basics",
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"Probability_Distributions.rst": "Basics",
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"Gaussian_Processes.rst": "Basics",
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"data_container": "Basics",
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"sampling_compound_step": "Deep dives",
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"sampling_callback": "Deep dives",
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"sampler-stats": "Deep dives",
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"Diagnosing_biased_Inference_with_Divergences": "Deep dives",
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"pymc3_howto/data_container": "Basics",
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"pymc3_howto/sampling_compound_step": "Deep dives",
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"pymc3_howto/sampling_callback": "Deep dives",
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"diagnostics_and_criticism/sampler-stats": "Deep dives",
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"diagnostics_and_criticism/Diagnosing_biased_Inference_with_Divergences": "Deep dives",
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"Advanced_usage_of_Theano_in_PyMC3.rst": "Deep dives",
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"getting_started": "Deep dives",
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"ODE_API_shapes_and_benchmarking": "Deep dives",
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"DEMetropolisZ_EfficiencyComparison": "Deep dives",
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"DEMetropolisZ_tune_drop_fraction": "Deep dives",
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"factor_analysis": "Deep dives",
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"blackbox_external_likelihood": "How-To",
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"profiling": "How-To",
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"howto_debugging": "How-To",
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"model_averaging": "How-To",
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"updating_priors": "How-To",
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"lasso_block_update": "How-To"
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"ode_models/ODE_API_shapes_and_benchmarking": "Deep dives",
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"samplers/DEMetropolisZ_EfficiencyComparison": "Deep dives",
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"samplers/DEMetropolisZ_tune_drop_fraction": "Deep dives",
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"case_studies/factor_analysis": "Deep dives",
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"case_studies/blackbox_external_likelihood": "How-To",
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"pymc3_howto/profiling": "How-To",
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"pymc3_howto/howto_debugging": "How-To",
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"diagnostics_and_criticism/model_averaging": "How-To",
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"pymc3_howto/updating_priors": "How-To",
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"pymc3_howto/lasso_block_update": "How-To"
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}

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