Author:
Kühnel Line,Fletcher Tom,Joshi Sarang,Sommer Stefan
Publisher
Springer International Publishing
Reference29 articles.
1. Shao, H., Kumar, A., Thomas Fletcher, P.: The Riemannian geometry of deep generative models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 315–323 (2018)
2. Chen, N., Klushyn, A., Kurle, R., Jiang, X., Bayer, J., van der Smagt, P.: Metrics for deep generative models. In: AISTAT 2018, November 2017
3. Arvanitidis, G., Hansen, L.K., Hauberg, S.: Latent space oddity: on the curvature of deep generative models. In: ICLR 2018. arXiv:1710.11379, October 2017
4. Yang, T., Arvanitidis, G., Fu, D., Li, X., Hauberg, S.: Geodesic clustering in deep generative models. arXiv:1809.04747, September 2018
5. Shukla, A., Uppal, S., Bhagat, S., Anand, S., Turaga, P.: Geometry of deep generative models for disentangled representations. In: Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing, ser. ICVGIP 2018. New York, NY, USA. Association for Computing Machinery, pp. 1–8, December 2018