YerevaNN /jɛɾɛvɑnˈɛn/ is a non-profit computer science and mathematics research lab based in Yerevan, Armenia.
Research
- Machine learning algorithms
- Characterization of the failure modes of domain generalization algorithms
[preprint],
accepted at CVPR'22
(with USC ISI).
- WARP: a parameter-efficient method for transfer learning in NLP.
Published in ACL'21
(with USC ISI)
- Theoretical analysis of the detection of the feature matching map in presence of outliers
[preprint]
(with ENSAE-CREST)
- Robust classification under class-dependent domain shift
[preprint]
(with USC ISI). Presented at ICML 2020
UDL Workshop
- A novel robust estimator of the mean of a multivariate Gaussian distribution.
Published in Annals of Statistics.
(with ENSAE-CREST)
- T-Corex: a novel method for temporal covariance estimation using information theoretic apparatus
[preprint]
[code]
(with USC ISI)
- Machine learning for biomedical data
- Development of Armenian treebanks
- Student projects
Visit our blog and GitHub for more.
The handwritten digits in the background are generated by deep convolutional generative adversarial networks [paper] [code]