Search Results for author:
Found 2 papers, 0 papers with code
Integrating molecular models into CryoEM heterogeneity analysis using scalable high-resolution deep Gaussian mixture models
Resolving the structural variability of proteins is often key to understanding the structure-function relationship of those macromolecular machines.
Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks
We consider the statistical problem of learning common source of variability in data which are synchronously captured by multiple sensors, and demonstrate that Siamese neural networks can be naturally applied to this problem.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
