No photo of Vikas Verma

Vikas Verma

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

20172023

Research activity per year

Filter
Conference article in proceedings

Search results

  • 2023

    MixupE: Understanding and improving Mixup from directional derivative perspective

    Zou, Y., Verma, V., Mittal, S., Tang, W. H., Pham, H., Kannala, J., Bengio, Y., Solin, A. & Kawaguchi, K., Aug 2023, Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023). JMLR, p. 2597-2607 (Proceedings of Machine Learning Research ; vol. 216).

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

    Open Access
    File
    32 Downloads (Pure)
  • 2022

    PatchUp : A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks

    Faramarzi, M., Amini, M., Badrinaaraayanan, A., Verma, V. & Chandar, S., 30 Jun 2022, AAAI-22 Technical Tracks 1. AAAI Press, p. 589-597 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 36).

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

    Open Access
    7 Citations (Scopus)
  • 2021

    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 Press, p. 10024-10032 9 p. (AAAI Conference on Artificial Intelligence; vol. 35).

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

    Open Access
    38 Citations (Scopus)
  • 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. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

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

    Open Access
    41 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. JMLR, 12 p. (Proceedings of Machine Learning Research; vol. 139).

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

    Open Access
    File
    44 Downloads (Pure)
  • 2020

    InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

    Sun, F-Y., Hoffman, J., Verma, V. & Tang, J., 2020, International Conference on Learning Representations. OpenReview.net

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsProfessional

    Open Access
  • SketchTransfer: A challenging new task for exploring detail-invariance and the abstractions learned by deep networks

    Lamb, A., Ozair, S., Verma, V. & Ha, D., Mar 2020, Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020. IEEE, p. 952-961 10 p. 9093327

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

    6 Citations (Scopus)
  • 2019

    Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy

    Verma, V., Lamb, A., Kannala, J. & Bengio, Y., 2019, AISec'19: Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security. ACM, p. 95-103

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

    Open Access
    File
    250 Downloads (Pure)
  • Interpolation consistency training for semi-supervised learning

    Verma, V., Lamb, A., Kannala, J., Bengio, Y. & Lopez-Paz, D., 2019, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19). IJCAI, p. 3635-3641

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

    Open Access
  • Manifold Mixup: Better Representations by Interpolating Hidden States

    Verma, V., Lamb, A., Beckham, C., Najafi, A., Mitliagkas, I., Lopez-Paz, D. & Bengio, Y., 2019, Proceedings of the 36th International Conference on Machine Learning. JMLR, (Proceedings of Machine Learning Research; vol. 97).

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

    Open Access
    File
    410 Downloads (Pure)
  • On Adversarial Mixup Resynthesis

    Beckham, C., Honari, S., Verma, V., Lamb, A., Ghadiri, F., Hjelm, R. D., Bengio, Y. & Pal, C., 2019, 33rd Conference on Neural Information Processing Systems: NeurIPS 2019 . Neural Information Processing Systems Foundation, (Advances in Neural Information Processing Systems).

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

    Open Access
Your message has successfully been sent.
Your message was not sent due to an error.