Search Results for author:
Found 2 papers, 1 papers with code
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning
We argue that typical data augmentation techniques (e. g., edge dropping) in GCL cannot generate diverse enough contrastive views to filter out noises.
xTrimoABFold: De novo Antibody Structure Prediction without MSA
Its improvement in both accuracy and efficiency makes it a valuable tool for de novo antibody design and could make further improvements in immuno-theory.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
