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@karm-patel
Last active June 25, 2022 20:13
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0 2.1 ['student_laplace_pdf_plot.ipynb']
  • 1 2.2 ['sub_super_gauss_plot.ipynb']
  • 2 2.3 ['pareto_dist_plot.ipynb']
  • 3 2.4 ['zipfs_law_plot.ipynb']
  • 4 2.5 ['dirichlet_3d_triangle_plot.ipynb', 'dirichlet_3d_spiky_plot.ipynb']
  • 5 2.7 ['bayes_change_of_var.ipynb']
  • 6 2.8 ['ecdf_sample.ipynb']
  • 7 2.11 ['ngram_character_demo.ipynb']
  • 8 2.12 ['bigram_hinton_diagram.ipynb']
  • 9 3.1 ['linreg_post_pred_plot.ipynb']
  • 10 3.2 ['bimodal_dist_plot.ipynb', 'gamma_dist_plot.ipynb']
  • 11 3.4 ['gauss_infer_1d.ipynb']
  • 12 3.5 ['gauss_seq_update_sigma_1d.ipynb']
  • 13 3.6 ['nix_plots.ipynb']
  • 14 3.7 ['lkj_numpyro.ipynb']
  • 15 3.8 ['maxent_priors.ipynb']
  • 16 3.9 ['jeffreys_prior_binomial.ipynb']
  • 17 3.11 ['hbayes_binom_rats_pymc3.ipynb']
  • 18 3.12 ['schools8_pymc3.ipynb']
  • 19 3.13 ['schools8_pymc3.ipynb']
  • 20 3.14 ['schools8_pymc3.ipynb']
  • 21 3.16 ['ebBinom.ipynb']
  • 22 3.19 ['newcomb_plugin_demo.ipynb']
  • 23 3.2 ['linreg_divorce_ppc_numpyro.ipynb']
  • 24 4.2 ['student_pgm.ipynb']
  • 25 4.6 ['berksons_gaussian.ipynb']
  • 26 4.7 ['student_pgm.ipynb']
  • 27 4.16 ['gibbs_demo_ising.ipynb']
  • 28 4.17 ['gibbs_demo_potts_jax.ipynb']
  • 29 4.18 ['hopfield_demo.ipynb']
  • 30 4.2 ['rbm_contrastive_divergence.ipynb']
  • 31 4.26 ['ising_image_denoise_demo.ipynb']
  • 32 5.3 ['bernoulli_entropy_fig.ipynb']
  • 33 5.8 ['error_correcting_code_demo.ipynb']
  • 34 5.1 ['VIBDemo2021.ipynb']
  • 35 6.3 ['nat_grad_demo.ipynb']
  • 36 6.6 ['emLogLikelihoodMax.ipynb']
  • 37 6.7 ['gauss_imputation_em_demo.ipynb']
  • 38 6.8 ['var_em_bound.ipynb']
  • 39 6.13 ['simulated_annealing_2d_demo.ipynb']
  • 40 6.14 ['simulated_annealing_2d_demo.ipynb']
  • 41 6.15 ['simulated_annealing_2d_demo.ipynb']
  • 42 7.2 ['laplace_approx_beta_binom_jax.ipynb']
  • 43 7.3 ['advi_beta_binom_jax.ipynb']
  • 44 7.4 ['hmc_beta_binom_blackjax.ipynb']
  • 45 8.2 ['casino_hmm.ipynb']
  • 46 8.6 ['kf_tracking.ipynb']
  • 47 8.7 ['discretized_ssm.ipynb']
  • 48 8.8 ['discretized_ssm.ipynb']
  • 49 8.12 ['gauss-bp-1d-line.ipynb']
  • 50 9.3 ['ising_image_denoise_demo.ipynb']
  • 51 9.5 ['unigauss_vb_demo.ipynb']
  • 52 9.7 ['variational_mixture_gaussians_demo.ipynb']
  • 53 9.8 ['variational_mixture_gaussians_demo.ipynb']
  • 54 9.9 ['variational_mixture_gaussians_demo.ipynb']
  • 55 9.13 ['vb_gmm_tfp.ipynb']
  • 56 9.15 ['svi_gmm_demo_2d_tfp.ipynb']
  • 57 9.18 ['kl_pq_gauss.ipynb']
  • 58 10.1 ['mc_estimate_pi.ipynb']
  • 59 10.2 ['mc_accuracy_demo.ipynb']
  • 60 10.4 ['rejection_sampling_demo.ipynb']
  • 61 10.5 ['ars_envelope.ipynb', 'ars_demo.ipynb']
  • 62 11.1 ['mcmc_gmm_demo.ipynb']
  • 63 11.3 ['ising_image_denoise_demo.ipynb']
  • 64 11.4 ['mcmc_gmm_demo.ipynb']
  • 65 11.5 ['gibbs_gauss_demo.ipynb']
  • 66 11.8 ['slice_sampling_demo_1d.ipynb']
  • 67 11.9 ['slice_sampling_demo_2d.ipynb']
  • 68 11.12 ['random_walk_integers.ipynb']
  • 69 11.14 ['mcmc_traceplots_unigauss_numpyro.ipynb']
  • 70 11.15 ['mcmc_traceplots_unigauss_numpyro.ipynb']
  • 71 11.16 ['mcmc_traceplots_unigauss_numpyro.ipynb']
  • 72 11.17 ['mcmc_traceplots_unigauss_numpyro.ipynb']
  • 73 11.19 ['mcmc_gmm_demo.ipynb']
  • 74 11.2 ['neals_funnel.ipynb', 'funnel_numpyro.ipynb']
  • 75 12.1 ['bootstrap_filter.ipynb']
  • 76 12.2 ['sis_vs_smc.ipynb']
  • 77 12.3 ['sis_vs_smc.ipynb']
  • 78 12.6 ['smc_tempered_1d_bimodal.ipynb']
  • 79 12.7 ['smc_tempered_1d_bimodal.ipynb']
  • 80 12.8 ['smc_ibis_1d.ipynb']
  • 81 13.3 ['softmax_plot.ipynb']
  • 82 14.1 ['linreg_height_weight_numpyro.ipynb']
  • 83 14.2 ['linreg_height_weight_numpyro.ipynb']
  • 84 14.5 ['logreg_prior_offset.ipynb', 'logreg_prior.ipynb']
  • 85 14.6 ['logreg_laplace_demo.ipynb']
  • 86 14.7 ['logreg_laplace_demo.ipynb']
  • 87 14.8 ['logreg_iris_bayes_2d_pymc3.ipynb']
  • 88 14.1 ['adf_logistic_regression_demo.ipynb']
  • 89 14.11 ['adf_logistic_regression_demo.ipynb']
  • 90 14.12 ['probit_plot.ipynb']
  • 91 14.13 ['probitRegDemo.ipynb']
  • 92 14.15 ['linreg_hierarchical_non_centered_blackjax.ipynb']
  • 93 14.16 ['linreg_hierarchical_non_centered_blackjax.ipynb']
  • 94 14.17 ['linreg_hierarchical_non_centered_blackjax.ipynb']
  • 95 15.2 ['activation_fun_deriv_jax.ipynb']
  • 96 15.11 ['lecun1989_flax.ipynb']
  • 97 16.1 ['mlpPriorsDemo2.ipynb']
  • 98 16.5 ['randomized_priors.ipynb']
  • 99 16.2 ['ekf_mlp.ipynb']
  • 100 16.21 ['bnn_hierarchical_blackjax.ipynb']
  • 101 16.22 ['hbayes_figures2.ipynb']
  • 102 16.23 ['bnn_hierarchical_blackjax.ipynb']
  • 103 16.24 ['bnn_hierarchical_blackjax.ipynb']
  • 104 17.2 ['gprDemoArd.ipynb']
  • 105 17.3 ['gpKernelPlot.ipynb']
  • 106 17.4 ['gpKernelPlot.ipynb']
  • 107 17.5 ['combining_kernels_by_multiplication.ipynb']
  • 108 17.6 ['combining_kernels_by_summation.ipynb']
  • 109 17.7 ['gprDemoNoiseFree.ipynb']
  • 110 17.8 ['krr_vs_gpr.ipynb']
  • 111 17.9 ['gpc_demo_2d_sklearn.ipynb']
  • 112 17.1 ['gp_poisson_1d.ipynb']
  • 113 17.11 ['gp_spatial_demo.ipynb']
  • 114 17.15 ['gprDemoChangeHparams.ipynb']
  • 115 17.16 ['gpr_demo_marglik.ipynb']
  • 116 17.18 ['gp_kernel_opt.ipynb']
  • 117 17.23 ['gp_spectral_mixture.ipynb']
  • 118 17.26 ['gp_deep_kernel_learning.ipynb']
  • 119 18.8 ['bnn_mnist_sgld.ipynb']
  • 120 18.9 ['bnn_mnist_sgld.ipynb']
  • 121 19.4 ['parzen_window_demo2.ipynb']
  • 122 19.7 ['vae_compare_results.ipynb']
  • 123 19.8 ['vae_celeba_lightning.ipynb']
  • 124 20.3 ['vae_compare_results.ipynb']
  • 125 20.4 ['vae_compare_results.ipynb']
  • 126 20.7 ['vae_latent_space.ipynb']
  • 127 20.18 ['vdvae_flax_demo_cifar.ipynb']
  • 128 20.21 ['quantized_autoencoder_mnist.ipynb']
  • 129 22.1 ['flow_2d_mlp.ipynb']
  • 130 22.4 ['flow_spline_mnist_jax.ipynb']
  • 131 22.8 ['two_moons_normalizingFlow.ipynb']
  • 132 23.3 ['score_matching_swiss_roll.ipynb']
  • 133 25.1 ['genmo_types_implicit_explicit.ipynb']
  • 134 25.4 ['IPM_divergences.ipynb']
  • 135 25.5 ['IPM_divergences.ipynb']
  • 136 25.6 ['GAN_loss_types.ipynb']
  • 137 25.7 ['gan_mixture_of_gaussians.ipynb']
  • 138 25.8 ['DiracGAN.ipynb']
  • 139 25.9 ['DiracGAN.ipynb']
  • 140 27.1 ['gmm_plot_demo.ipynb']
  • 141 27.2 ['gmm_2d.ipynb']
  • 142 27.3 ['mix_bernoulli_em_mnist.ipynb']
  • 143 27.1 ['binary_fa_demo.ipynb']
  • 144 27.11 ['gplvm_mocap.ipynb']
  • 145 27.13 ['mixPpcaDemo.ipynb']
  • 146 27.16 ['mix_PPCA_celeba.ipynb']
  • 147 27.18 ['mix_PPCA_celeba.ipynb']
  • 148 27.19 ['mix_PPCA_celeba.ipynb']
  • 149 27.31 ['ica_demo.ipynb']
  • 150 27.32 ['ica_demo_uniform.ipynb']
  • 151 27.33 ['sparse_dict_demo.ipynb']
  • 152 28.3 ['bernoulli_hmm_example.ipynb']
  • 153 28.4 ['hmm_gauss2d.ipynb']
  • 154 28.5 ['hmm_poisson_changepoint_jax.ipynb']
  • 155 28.6 ['hmm_poisson_changepoint_jax.ipynb']
  • 156 28.7 ['hmm_poisson_changepoint_jax.ipynb']
  • 157 28.8 ['kf_tracking.ipynb']
  • 158 28.9 ['kf_spiral.ipynb']
  • 159 28.1 ['kf_linreg.ipynb']
  • 160 28.11 ['ekf_vs_ukf.ipynb', 'bootstrap_filter.ipynb']
  • 161 28.15 ['gp_mauna_loa.ipynb']
  • 162 29.8 ['ggm_lasso_demo.ipynb']
  • 163 29.9 ['newsgroupsVisualize.ipynb']
  • 164 29.1 ['relevance_network_newsgroup_demo.ipynb']
  • 165 29.12 ['chow_liu_tree_demo.ipynb']
  • 166 30.3 ['stick_breaking_demo.ipynb']
  • 167 30.4 ['dpm_sample_demo.ipynb']
  • 168 33.3 ['ab_test_demo.ipynb']
  • 169 33.7 ['thompson_sampling_linear_gaussian.ipynb']
  • GAN_JAX_CelebA_demo.ipynb
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