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Fixed header.
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‎popprior_mf/compute_llhood.py

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"""
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Compute the heldout llhood for a given model.
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@Author: De-identified Author
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@Author: Sohrab Salehi [email protected]
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"""
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import argparse

‎popprior_mf/data_utils.py

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# """
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# Data utilities for the project, including preprocessing, binarization
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# @Author: De-identified Author
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# @Author: Sohrab Salehi [email protected]
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# """
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import torch

‎popprior_mf/model_encoders.py

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- Encoder: the encoder network, a feedforward neural network that given the input X, outputs MEAN for the latent distibution.
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- Encoder_full: as encoder, but also outputs STDDEV for the latent distribution.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb_column.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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With EB prior only on the columns
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb_column_plus.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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With EB prior only on the columns
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb_plus.py

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Is a more true populatin prior, that is, instead of a VampPrior, it uses a mixture of the q's
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb_twin.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_eb_twin_plus.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_natural_eb_plus.py

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Is a more true populatin prior, that is, instead of a VampPrior, it uses a mixture of the q's
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_natural_eb_single.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_natural_eb_twin_plus.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_pmf_natural_eb_twin_single.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_population_prior.py

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"""
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Implements the Population Mixture of Priors.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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‎popprior_mf/model_population_prior_natural.py

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"""
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Implements the Population Mixture of Priors.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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‎popprior_mf/model_ppca_eb.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_eb_column.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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with just an EB prior on the global paramters.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_eb_column_plus.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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with just an EB prior on the global paramters.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_eb_plus.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference.
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Uses a population prior instead of a vamp prior.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_eb_twin.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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with the addition of a EB prior on the global paramters.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_eb_twin_plus.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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with the addition of a EB prior on the global paramters.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_natural_eb_single.py

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"""
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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_ppca_natural_eb_twin_single.py

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The Probabilistic Principal Component Analysis (PPCA) with an Emprical Bayes prior using variational inference
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with the addition of a EB prior on the global paramters.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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import torch

‎popprior_mf/model_skeleton.py

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3. Define the variational family q(Z|X) in the `__init__()` method of the [ObservedDistribution] instance by \
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equiping the each latent with the appropriate [VariationalFamilyDistribution] instance.
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@Author: De-identified Author
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@Author: Sohrab Salehi [email protected]
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"""
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‎popprior_mf/model_vampprior.py

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"""
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Implements the Variational Mixture of Posteriors Prior (VampPrior) model.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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‎popprior_mf/model_vampprior_natural.py

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"""
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Implements the Variational Mixture of Posteriors Prior (VampPrior) model.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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‎popprior_mf/model_vampprior_natural_single.py

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"""
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Implements the Variational Mixture of Posteriors Prior (VampPrior) model.
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Author: De-identified Author
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@Author: Sohrab Salehi ([email protected])
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"""
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‎popprior_mf/model_variational_family.py

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See here: https://pyro.ai/examples/sparse_gamma.html
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@Author: Sohrab Salehi [email protected]
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"""
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‎popprior_mf/model_variational_family_natural.py

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See here: https://pyro.ai/examples/sparse_gamma.html
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@Author: Sohrab Salehi [email protected]
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"""
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‎popprior_mf/param_generator.py

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"""
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Set of tools to generate files for a parameter sweep.
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@Author: Sohrab Salehi [email protected]
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"""
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import random

‎popprior_mf/setup_data.py

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"""
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Script to setup the data for experiments with CDM.
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@Author: Sohrab Salehi ([email protected])
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"""
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import re

‎popprior_mf/training_utils.py

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# """
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# Training utils
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# @Author: De-identified Author
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# @Author: Sohrab Salehi [email protected]
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# """
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import torch

‎popprior_mf/viz.py

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"""
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Set of visualizations methods for the VI in factor models.
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@Author: Sohrab Salehi [email protected]
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"""
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‎popprior_mf/viz_utils.py

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"""
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Utility functions for visualization of 2D matrices.
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@Author: Sohrab Salehi ([email protected])
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"""
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from sklearn.cluster import AgglomerativeClustering
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import matplotlib.pyplot as plt

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