dashboard_figures_book2.md

November 25, 2024 · View on GitHub

Instructions

Book2Dashboard

Total NotebooksLatexifiedJaxified
2037564
Chapter: 2_Probability
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student_laplace_pdf_plot.ipynb2.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/student_laplace_pdf_plot.png>, log
sub_super_gauss_plot.ipynb2.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/sub_super_gauss_plot.png>, log
pareto_dist_plot.ipynb2.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/pareto_dist_plot.png>, log
zipfs_law_plot.ipynb2.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/zipfs_law_plot.png>, log
gauss_plot_2d.ipynb2.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/gauss_plot_2d.png>, log
sensor_fusion_2d.ipynb2.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/sensor_fusion_2d.png>, log
wishart_plot.ipynb2.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/wishart_plot.png>, log
wishart_plot.ipynb2.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/wishart_plot.png>, log
dirichlet_3d_triangle_plot.ipynb2.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/dirichlet_3d_triangle_plot.png>, log
dirichlet_3d_spiky_plot.ipynb2.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/dirichlet_3d_spiky_plot.png>, log
dirichlet_samples_plot.ipynb2.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/dirichlet_samples_plot.png>, log
bayes_change_of_var.ipynb2.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/bayes_change_of_var.png>, log
ecdf_sample.ipynb2.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/ecdf_sample.png>, log
ngram_character_demo.ipynb2.17<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/ngram_character_demo.png>, log
bigram_hinton_diagram.ipynb2.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/02/bigram_hinton_diagram.png>, log
Chapter: 3_Bayesian statistics
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linreg_post_pred_plot.ipynb3.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/linreg_post_pred_plot.png>, log
bimodal_dist_plot.ipynb3.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/bimodal_dist_plot.png>, log
gamma_dist_plot.ipynb3.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/gamma_dist_plot.png>, log
gauss_infer_1d.ipynb3.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/gauss_infer_1d.png>, log
gauss_seq_update_sigma_1d.ipynb3.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/gauss_seq_update_sigma_1d.png>, log
nix_plots.ipynb3.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/nix_plots.png>, log
gauss_infer_2d.ipynb3.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/gauss_infer_2d.png>, log
lkj_1d.ipynb3.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/lkj_1d.png>, log
maxent_priors.ipynb3.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/maxent_priors.png>, log
jeffreys_prior_binomial.ipynb3.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/jeffreys_prior_binomial.png>, log
hbayes_binom_rats.ipynb3.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/hbayes_binom_rats.png>, log
schools8.ipynb3.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/schools8.png>, log
schools8.ipynb3.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/schools8.png>, log
schools8.ipynb3.16<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/schools8.png>, log
eb_binom.ipynb3.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/eb_binom.png>, log
newcomb_plugin_demo.ipynb3.21<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/newcomb_plugin_demo.png>, log
linreg_divorce_ppc.ipynb3.22<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/03/linreg_divorce_ppc.png>, log
Chapter: 4_Probabilistic graphical models
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student_pgm.ipynb4.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/student_pgm.png>, log
berksons_gaussian.ipynb4.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/berksons_gaussian.png>, log
student_pgm.ipynb4.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/student_pgm.png>, log
gibbs_demo_ising.ipynb4.16<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/gibbs_demo_ising.png>, log
gibbs_demo_potts.ipynb4.17<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/gibbs_demo_potts.png>, log
hopfield_demo.ipynb4.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/hopfield_demo.png>, log
rbm_contrastive_divergence.ipynb4.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/rbm_contrastive_divergence.png>, log
ising_image_denoise_demo.ipynb4.26<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/04/ising_image_denoise_demo.png>, log
Chapter: 5_Information theory
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bernoulli_entropy_fig.ipynb5.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/05/bernoulli_entropy_fig.png>, log
newsgroups_visualize.ipynb5.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/05/newsgroups_visualize.png>, log
relevance_network_newsgroup_demo.ipynb5.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/05/relevance_network_newsgroup_demo.png>, log
error_correcting_code_demo.ipynb5.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/05/error_correcting_code_demo.png>, log
vib_demo_2021.ipynb5.12<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/05/vib_demo_2021.png>, log
Chapter: 6_Optimization
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nat_grad_demo.ipynb6.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/nat_grad_demo.png>, log
em_log_likelihood_max.ipynb6.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/em_log_likelihood_max.png>, log
gauss_imputation_em_demo.ipynb6.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/gauss_imputation_em_demo.png>, log
var_em_bound.ipynb6.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/var_em_bound.png>, log
simulated_annealing_2d_demo.ipynb6.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/simulated_annealing_2d_demo.png>, log
simulated_annealing_2d_demo.ipynb6.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/simulated_annealing_2d_demo.png>, log
simulated_annealing_2d_demo.ipynb6.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/06/simulated_annealing_2d_demo.png>, log
Chapter: 7_Inference algorithms: an overview
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laplace_approx_beta_binom.ipynb7.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/07/laplace_approx_beta_binom.png>, log
advi_beta_binom.ipynb7.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/07/advi_beta_binom.png>, log
hmc_beta_binom.ipynb7.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/07/hmc_beta_binom.png>, log
Chapter: 8_Inference for state-space models
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casino_hmm.ipynb8.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/casino_hmm.png>, log
kf_tracking.ipynb8.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/kf_tracking.png>, log
discretized_ssm_student.ipynb8.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/discretized_ssm_student.png>, log
discretized_ssm_student.ipynb8.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/discretized_ssm_student.png>, log
ekf_vs_ukf.ipynb8.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/ekf_vs_ukf.png>, log
pendulum_1d.ipynb8.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/pendulum_1d.png>, log
ekf_vs_ukf.ipynb8.17<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/ekf_vs_ukf.png>, log
adf_logistic_regression_demo.ipynb8.22<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/adf_logistic_regression_demo.png>, log
adf_logistic_regression_demo.ipynb8.23<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/08/adf_logistic_regression_demo.png>, log
Chapter: 9_Inference for graphical models
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gauss-bp-1d-line.ipynb9.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/09/gauss-bp-1d-line.png>, log
Chapter: 10_Variational inference
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ising_image_denoise_demo.ipynb10.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/ising_image_denoise_demo.png>, log
unigauss_vb_demo.ipynb10.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/unigauss_vb_demo.png>, log
variational_mixture_gaussians_demo.ipynb10.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/variational_mixture_gaussians_demo.png>, log
variational_mixture_gaussians_demo.ipynb10.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/variational_mixture_gaussians_demo.png>, log
variational_mixture_gaussians_demo.ipynb10.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/variational_mixture_gaussians_demo.png>, log
vb_gmm.ipynb10.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/vb_gmm.png>, log
svi_gmm_demo_2d.ipynb10.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/svi_gmm_demo_2d.png>, log
kl_pq_gauss.ipynb10.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/10/kl_pq_gauss.png>, log
Chapter: 11_Monte Carlo inference
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mc_estimate_pi.ipynb11.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/11/mc_estimate_pi.png>, log
mc_accuracy_demo.ipynb11.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/11/mc_accuracy_demo.png>, log
rejection_sampling_demo.ipynb11.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/11/rejection_sampling_demo.png>, log
ars_envelope.ipynb11.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/11/ars_envelope.png>, log
ars_demo.ipynb11.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/11/ars_demo.png>, log
Chapter: 12_Markov Chain Monte Carlo inference
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mcmc_gmm_demo.ipynb12.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_gmm_demo.png>, log
ising_image_denoise_demo.ipynb12.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/ising_image_denoise_demo.png>, log
mcmc_gmm_demo.ipynb12.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_gmm_demo.png>, log
gibbs_gauss_demo.ipynb12.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/gibbs_gauss_demo.png>, log
slice_sampling_demo_1d.ipynb12.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/slice_sampling_demo_1d.png>, log
slice_sampling_demo_2d.ipynb12.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/slice_sampling_demo_2d.png>, log
random_walk_integers.ipynb12.12<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/random_walk_integers.png>, log
mcmc_traceplots_unigauss.ipynb12.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_traceplots_unigauss.png>, log
mcmc_traceplots_unigauss.ipynb12.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_traceplots_unigauss.png>, log
mcmc_traceplots_unigauss.ipynb12.16<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_traceplots_unigauss.png>, log
mcmc_traceplots_unigauss.ipynb12.17<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_traceplots_unigauss.png>, log
rhat_slow_mixing_chains.ipynb12.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/rhat_slow_mixing_chains.png>, log
mcmc_gmm_demo.ipynb12.19<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/mcmc_gmm_demo.png>, log
neals_funnel.ipynb12.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/12/neals_funnel.png>, log
Chapter: 13_Sequential Monte Carlo inference
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sis_vs_smc.ipynb13.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/sis_vs_smc.png>, log
sis_vs_smc.ipynb13.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/sis_vs_smc.png>, log
pf_guided_neural_decoding.ipynb13.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/pf_guided_neural_decoding.png>, log
rbpf_maneuver.ipynb13.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/rbpf_maneuver.png>, log
bootstrap_filter_maneuver.ipynb13.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/bootstrap_filter_maneuver.png>, log
rbpf_maneuver_demo.ipynb13.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/rbpf_maneuver_demo.png>, log
rbpf_maneuver_demo.ipynb13.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/rbpf_maneuver_demo.png>, log
smc_tempered_1d_bimodal.ipynb13.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/smc_tempered_1d_bimodal.png>, log
smc_tempered_1d_bimodal.ipynb13.12<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/smc_tempered_1d_bimodal.png>, log
smc_ibis_1d.ipynb13.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/13/smc_ibis_1d.png>, log
Chapter: 14_Predictive models: an overview
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Chapter: 15_Generalized linear models
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linreg_height_weight.ipynb15.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/linreg_height_weight.png>, log
logreg_prior_offset.ipynb15.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/logreg_prior_offset.png>, log
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logreg_laplace_demo.ipynb15.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/logreg_laplace_demo.png>, log
logreg_laplace_demo.ipynb15.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/logreg_laplace_demo.png>, log
logreg_iris_bayes_2d.ipynb15.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/logreg_iris_bayes_2d.png>, log
probit_plot.ipynb15.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/probit_plot.png>, log
probit_reg_demo.ipynb15.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/probit_reg_demo.png>, log
linreg_hierarchical_non_centered.ipynb15.12<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/linreg_hierarchical_non_centered.png>, log
linreg_hierarchical_non_centered.ipynb15.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/linreg_hierarchical_non_centered.png>, log
linreg_hierarchical_non_centered.ipynb15.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/15/linreg_hierarchical_non_centered.png>, log
Chapter: 16_Deep neural networks
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lecun1989.ipynb16.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/16/lecun1989.png>, log
Chapter: 17_Bayesian neural networks
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randomized_priors.ipynb17.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/randomized_priors.png>, log
ekf_mlp.ipynb17.21<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/ekf_mlp.png>, log
bnn_hierarchical.ipynb17.22<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/bnn_hierarchical.png>, log
hbayes_figures2.ipynb17.23<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/hbayes_figures2.png>, log
bnn_hierarchical.ipynb17.24<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/bnn_hierarchical.png>, log
bnn_hierarchical.ipynb17.25<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/17/bnn_hierarchical.png>, log
Chapter: 18_Gaussian processes
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gp_kernel_plot.ipynb18.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_kernel_plot.png>, log
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combining_kernels_by_multiplication.ipynb18.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/combining_kernels_by_multiplication.png>, log
combining_kernels_by_summation.ipynb18.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/combining_kernels_by_summation.png>, log
gpr_demo_noise_free.ipynb18.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gpr_demo_noise_free.png>, log
krr_vs_gpr.ipynb18.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/krr_vs_gpr.png>, log
gpc_demo_2d.ipynb18.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gpc_demo_2d.png>, log
gp_poisson_1d.ipynb18.1<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_poisson_1d.png>, log
gp_spatial_demo.ipynb18.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_spatial_demo.png>, log
gpr_demo_change_hparams.ipynb18.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gpr_demo_change_hparams.png>, log
gpr_demo_marglik.ipynb18.16<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gpr_demo_marglik.png>, log
gp_kernel_opt.ipynb18.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_kernel_opt.png>, log
gp_spectral_mixture.ipynb18.23<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_spectral_mixture.png>, log
gp_deep_kernel_learning.ipynb18.26<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_deep_kernel_learning.png>, log
deepgp_stepdata.ipynb18.32<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/deepgp_stepdata.png>, log
gp_mauna_loa.ipynb18.34<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/18/gp_mauna_loa.png>, log
Chapter: 19_Beyond the iid assumption
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bnn_mnist_sgld.ipynb19.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/19/bnn_mnist_sgld.png>, log
Chapter: 20_Generative models: an overview
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vae_compare_results.ipynb20.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/20/vae_compare_results.png>, log
vae_celebA_lightning.ipynb20.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/20/vae_celebA_lightning.png>, log
Chapter: 21_Variational autoencoders
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vae_compare_results.ipynb21.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/21/vae_compare_results.png>, log
vae_latent_space.ipynb21.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/21/vae_latent_space.png>, log
vdvae_demo_cifar.ipynb21.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/21/vdvae_demo_cifar.png>, log
quantized_autoencoder_mnist.ipynb21.21<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/21/quantized_autoencoder_mnist.png>, log
Chapter: 23_Normalizing Flows
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flow_spline_mnist.ipynb23.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/23/flow_spline_mnist.png>, log
two_moons_normalizing_flow.ipynb23.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/23/two_moons_normalizing_flow.png>, log
Chapter: 24_Energy-based models
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Chapter: 25_Diffusion models
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Chapter: 26_Generative adversarial networks
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ipm_divergences.ipynb26.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/ipm_divergences.png>, log
ipm_divergences.ipynb26.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/ipm_divergences.png>, log
gan_loss_types.ipynb26.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/gan_loss_types.png>, log
gan_mixture_of_gaussians.ipynb26.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/gan_mixture_of_gaussians.png>, log
dirac_gan.ipynb26.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/dirac_gan.png>, log
dirac_gan.ipynb26.9<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/26/dirac_gan.png>, log
Chapter: 28_Latent factor models
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gmm_2d.ipynb28.2<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/gmm_2d.png>, log
mix_bernoulli_em_mnist.ipynb28.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/mix_bernoulli_em_mnist.png>, log
mix_ppca_demo.ipynb28.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/mix_ppca_demo.png>, log
mix_ppca_celebA.ipynb28.11<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/mix_ppca_celebA.png>, log
mix_ppca_celebA.ipynb28.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/mix_ppca_celebA.png>, log
mix_ppca_celebA.ipynb28.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/mix_ppca_celebA.png>, log
binary_fa_demo.ipynb28.18<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/binary_fa_demo.png>, log
gplvm_mocap.ipynb28.19<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/gplvm_mocap.png>, log
ica_demo.ipynb28.31<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/ica_demo.png>, log
ica_demo_uniform.ipynb28.32<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/ica_demo_uniform.png>, log
sparse_dict_demo.ipynb28.33<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/28/sparse_dict_demo.png>, log
Chapter: 29_State-space models
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hmm_gaussian_2d.ipynb29.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_gaussian_2d.png>, log
hmm_ar.ipynb29.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_ar.png>, log
hmm_ar.ipynb29.5<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_ar.png>, log
hmm_poisson_changepoint.ipynb29.6<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_poisson_changepoint.png>, log
hmm_poisson_changepoint.ipynb29.7<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_poisson_changepoint.png>, log
hmm_poisson_changepoint.ipynb29.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_poisson_changepoint.png>, log
hmm_casino_training.ipynb29.13<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_casino_training.png>, log
hmm_casino_training.ipynb29.14<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_casino_training.png>, log
hmm_self_loop_dist.ipynb29.15<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/hmm_self_loop_dist.png>, log
changepoint_detection.ipynb29.22<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/changepoint_detection.png>, log
kf_tracking.ipynb29.23<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/kf_tracking.png>, log
kf_linreg.ipynb29.24<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/kf_linreg.png>, log
kf_parallel.ipynb29.26<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/kf_parallel.png>, log
poisson_lds_example.ipynb29.3<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/poisson_lds_example.png>, log
poisson_lds_example.ipynb29.31<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/poisson_lds_example.png>, log
sts.ipynb29.33<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/sts.png>, log
sts.ipynb29.34<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/sts.png>, log
sts.ipynb29.35<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/sts.png>, log
sts.ipynb29.36<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/sts.png>, log
causal_impact.ipynb29.41<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/29/causal_impact.png>, log
Chapter: 30_Graph learning
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Chapter: 31_Non-parametric Bayesian models
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dp_mixgauss_sample.ipynb31.4<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/31/dp_mixgauss_sample.png>, log
Chapter: 34_Decision making under uncertainty
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thompson_sampling_linear_gaussian.ipynb34.8<img width="20" alt="image" src=https://raw.githubusercontent.com/probml/pyprobml/workflow_testing_indicator/notebooks/book2/34/thompson_sampling_linear_gaussian.png>, log