Man pages for ML2Pvae
Variational Autoencoder Models for IRT Parameter Estimation
| build_hidden_encoder | Build the encoder for a VAE |
| build_vae_correlated | Build a VAE that fits to a normal, full covariance N(m,S)... |
| build_vae_independent | Build a VAE that fits to a standard N(0,I) latent... |
| correlation_matrix | Simulated latent abilities correlation matrix |
| diff_true | Simulated difficulty parameters |
| disc_true | Simulated discrimination parameters |
| dot-onLoad | Display a message upon loading package |
| get_ability_parameter_estimates | Feed forward response sets through the encoder, which outputs... |
| get_item_parameter_estimates | Get trainable variables from the decoder, which serve as item... |
| ML2Pvae | ML2Pvae: A package for creating a VAE whose decoder recovers... |
| q_1pl_constraint | A custom kernel constraint function that forces nonzero... |
| q_constraint | A custom kernel constraint function that restricts weights... |
| q_matrix | Simulated Q-matrix |
| responses | Response data |
| sampling_correlated | A reparameterization in order to sample from the learned... |
| sampling_independent | A reparameterization in order to sample from the learned... |
| theta_true | Simulated ability parameters |
| train_model | Trains a VAE or autoencoder model. This acts as a wrapper for... |
| vae_loss_correlated | A custom loss function for a VAE learning a multivariate... |
| vae_loss_independent | A custom loss function for a VAE learning a standard normal... |
| validate_inputs | Give error messages for invalid inputs in exported functions. |
