research lab

YerevaNN /jɛɾɛvɑnˈɛn/ is a machine learning research center based in Yerevan, Armenia. Read more about our plans to establish an AI Institute. YerevaNN is a non-profit funded by research grants, academic partnerships and generous donations. Here are the easiest ways to support us.


Machine learning for biomedical data Machine learning under domain shift
  • [2023] Identifying and disentangling spurious features in pretrained image representations. [preprint] (with Meta AI and USC ISI). Accepted at ICML 2023 Workshop on Spurious Correlations, Invariance and Stability.
  • [2021] Characterization of the failure modes of domain generalization algorithms. Published in CVPR'22 (with USC ISI).
  • [2020] Robust classification under class-dependent domain shift [preprint] (with USC ISI). Presented at ICML 2020 UDL Workshop
Machine learning algorithms
  • [2023] Scaling laws for mixed-modal language models. [preprint] (with Meta AI)
  • [2023] Wireless non-line-of-sight localization of a device using a single antenna in an urban environment Accepted at IEEE Big Data Service 2023. [preprint] (with Yerevan State University and CNR Institute of Informatics and Telematics)
  • [2022] Matching map recovery with an unknown number of outliers. Published in AISTATS'23 [preprint] (with ENSAE-CREST)
  • [2022] GradSkip: an extension of a local gradient method for distributed optimization that supports variable number of local gradient steps in each communication round. [preprint] (with KAUST)
  • [2021] WARP: a parameter-efficient method for transfer learning in NLP. Published in ACL'21 (with USC ISI)
  • [2021] Theoretical analysis of the detection of the feature matching map in presence of outliers. Published in Electronic Journal of Statistics (with ENSAE-CREST)
  • [2021] A survey of deep neural networks for semi-supervised image classification. Published in JUCS.
  • [2020] A novel robust estimator of the mean of a multivariate Gaussian distribution. Published in Annals of Statistics (with ENSAE-CREST)
  • [2019] T-Corex: a novel method for temporal covariance estimation using information theoretic apparatus [preprint] [code] (with USC ISI)
Development of Armenian treebanks


  • Hrant Khachatrian
  • Tigran Galstyan
  • Ani Tevosyan
  • Khazhak Galstyan
  • Knarik Mheryan
  • Philipp Guevorguian
  • Rafayel Mkrtchyan
  • Menua Bedrosian
  • Karen Hambardzumyan
  • Ani Vanyan
  • Gayane Chilingaryan
  • Rafayel Darbinyan
  • Alla Barseghyan
  • Vahan Huroyan
  • Hakob Tamazyan
  • Tatev Vardanyan
Alumni: Hrayr Harutyunyan, Gor Arakelyan, Martin Mirakyan, Ashot Matevosyan, Arshak Minasyan, Hovhannes Tamoyan, Davit Papikyan, Arto Maranjyan Please fill in this form if you are interested in joining YerevaNN.

The handwritten digits in the background are generated by deep convolutional generative adversarial networks [paper] [code]