Research interests
I do research in shape analysis and geometric deep learning. My work focuses on equivariance properties of neural networks,
but I have a broad interest in artificial intelligence and machine learning.
Recent publications
|
Poulenard, A., & Guibas, L. J. (2021). A Functional Approach to Rotation Equivariant Non-Linearities for Tensor Field Networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 13174-13183).
|
  |
|
R.Sajnani, A.Poulenard, J.Jain, R.Dua, L.Guibas, and S.Sridhar, ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes, arXiv preprint arXiv:2201.07788, (2022).
|
|
|
