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Found 4 papers, 2 papers with code
Multimodal Generative Models for Bankruptcy Prediction Using Textual Data
To solve this limitation, this research introduces the Conditional Multimodal Discriminative (CMMD) model that learns multimodal representations that embed information from accounting, market, and textual data modalities.
Discriminative Multimodal Learning via Conditional Priors in Generative Models
Deep generative models with latent variables have been used lately to learn joint representations and generative processes from multi-modal data.
Deep Generative Models for Reject Inference in Credit Scoring
Reject inference is the process of attempting to infer the creditworthiness status of the rejected applications.
Learning Latent Representations of Bank Customers With The Variational Autoencoder
We show that it is possible to steer the latent representations in the latent space of the VAE using the Weight of Evidence and forming a specific grouping of the data that reflects the customers' creditworthiness.
