Mengjiao Wang

Ms. Mengjiao Wang

Position:

Research Assistant / PhD Student

Email:

Biography

Mengjiao Wang obtained her BSc in Mathematics and Computer Science at Imperial College London in 2012. After working in industry for a couple of years, she completed her MSc in Computational Statistics and Machine Learning at University College London in 2015. Currently, she is a PhD candidate in Machine Learning and Vision at Imperial College London. Her research focus is on disentangling variations such as lighting, expression and identity from images.

Publications

Journal articles

Disentangling the Modes of Variation in Unlabelled Data

M. Wang, Y. Panagakis, P. Snape, S. Zafeiriou. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018.

Bibtex reference [hide]
@article{mwang2018disentangling,
    author = {M. Wang and Y. Panagakis and P. Snape and S. Zafeiriou},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    title = {Disentangling the Modes of Variation in Unlabelled Data},
    year = {2018},
}
Endnote reference [hide]

Conference articles

Learning the Multilinear Structure of Visual Data

M. Wang, Y. Panagakis, P. Snape, S. Zafeiriou. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). July 2017.

Bibtex reference [hide]
@inproceedings{meng2017,
    author = {M. Wang and Y. Panagakis and P. Snape and S. Zafeiriou},
    booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {July},
    title = {Learning the Multilinear Structure of Visual Data},
    year = {2017},
}
Endnote reference [hide]

Other publications

An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations

M. Wang, Z. Shu, Y. Panagakis, D. Samaras, S. Zafeiriou. arXiv preprint. 2017.

Bibtex reference [hide]
@conference{mwang17neurotensorial,
    author = {M. Wang and Z. Shu and Y. Panagakis and D. Samaras and S. Zafeiriou},
    booktitle = {arXiv preprint},
    journal = {arXiv preprint},
    title = {An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations},
    year = {2017},
}
Endnote reference [hide]