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Vikas Verma

  • Phone+358 50 4685953
  • Aalto SCI Computer Science Konemiehentie 2

20172022

Research activity per year

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Personal profile

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Master's degree, Engineering and Technology, Indian Institute of Technology Madras

Award Date: 22 Jul 2011

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  • Interpolation consistency training for semi-supervised learning

    Verma, V., Kawaguchi, K., Lamb, A., Kannala, J., Solin, A., Bengio, Y. & Lopez-Paz, D., 2022, In: Neural Networks. 145, p. 90-106

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
    File
    2 Citations (Scopus)
    56 Downloads (Pure)
  • GraphMix: Improved Training of GNNs for Semi-Supervised Learning

    Verma, V., Qu, M., Kawaguchi, K., Lamb, A., Bengio, Y., Kannala, J. & Tang, J., 2021, THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE. AAAI, p. 10024-10032 9 p. (AAAI Conference on Artificial Intelligence; vol. 35).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    2 Citations (Scopus)
  • GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning

    Verma, V., Qu, M., Lamb, A., Bengio, Y., Kannala, J. & Jian, T., 2021, AAAI.

    Research output: Working paperScientific

  • Interpolation-based Semi-supervised Learning for Object Detection

    Jeong, J., Verma, V., Hyun, M., Kannala, J. & Kwak, N., 13 Nov 2021, Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021. IEEE, p. 11597-11606 10 p. 9578767

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    3 Citations (Scopus)
  • Towards Domain-Agnostic Contrastive Learning

    Verma, V., Luong, M-T., Kawaguchi, K., Pham, H. & Le, Q. V., 2021, Proceedings of the 38 th International Conference on Machine Learning. 12 p. (Proceedings of Machine Learning Research; vol. 139).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    File
    7 Downloads (Pure)