Kluger Laboratory

Department of Pathology and Applied Math Program @Yale. Developing statistical, deep learning and spectral methods for analyzing biomedical datasets.

[Kluger Laboratory @KlugerLab]

Check out or new pre-print on Recovery of Latent Tree Models!
https://t.co/6ZyPf3p1Zh

[Kluger Laboratory @KlugerLab]

Congratulations to lab member @GCLinderman for their new publication, demonstrating analogous paradigms for preservation of global structure in t-SNE and UMAP. Read about it here: https://t.co/5le8GK1eqd

[George C. Linderman @GCLinderman]

A common misconception is that UMAP preserves global structure better than t-SNE. @hippopedoid and I showed that that this is only due to differences in default initialization.

Comment now published in @NatureBiotech: https://t.co/XwysMfgHj9
Thread: https://t.co/SUx3XgCOWH

[Dmitry Kobak @hippopedoid]

Mine and @GCLinderman's comment to the Becht et al. 2018 (@EtienneBecht) paper has finally appeared in @NatureBiotech after over a year of editorial considerations.

There is no response from the authors, so I assume we are all in agreement :-)

https://t.co/uHpwbq9bAE

[Wesley Lewis @ai_weslewis]

Very cool work on two-sample testing!

[Kluger Laboratory @KlugerLab]

Take a look at our new preprint on Local Two-Sample Testing on Graphs, now available on @arxiv:
https://t.co/2RTHE5QKpR