Role in this project:
ML Engineer Contributions:24 commits, 16 PRs, 40 pushes in 2 months
Contributions summary:Max focused on developing and improving a molecular autoencoder network for learning a continuous representation of molecular structures. Their contributions involved visualizing the model, refining the projection of the latent space, and implementing decoder functionality. They also worked on the preprocessing scripts and updated the model architecture, adding activations and refactoring components.