Variable Input Variable Output Neural Network for Learning from Heterogeneous Features with Multiple Losses

This is an ongoing project to construct deep learning models for learning from heterogeneous features (continuous or discrete) with missing values.

This project has shared the code base I had built for Multi-view Auto-Encoder.

This is a comprehensive framework with deep supervision (multi-losses) that can handle multi-view data with missing values.

Detailed documentation of each function is available in individual files.

If you have any questions or comments, feel free to contact me at tianlema@buffalo.edu