Chris Lin

Finally, we also performed zero-shot object localization by applying COCOA to image & text representations from a CLIP model. (6/6)

By visualizing important features that make an augmentation-transformed image similar to the original image (as opposed to random images), we showcased the utility of COCOA for understanding SimCLR representations under data augmentation. (5/n)

We have an upcoming paper at ICLR 2023 on a new feature attribution method for explaining representations learned by unsupervised models! arxiv.org/abs/2210.00107 This was joint work with the fantastic @HughChen18 @ChanwooKim_ and my advisor @suinleelab. (1/n)

Excited to share early results from a fantastic collaboration with @chrislin97! Over the past few months, we've been working on contrastiveVI (biorxiv.org/content/10.110…) - a deep generative model for performing contrastive analysis on scRNA-seq data. (1/11)