Lorentzian Fully Hyperbolic Generative Adversarial Network. (arXiv:2201.12825v2 [cs.LG] UPDATED)

With the recent advance of deep learning, neural networks have been
extensively used for data in non-Euclidean domains. In particular, hyperbolic
neural networks have proved successful in processing hierarchical information
of data. While a variety of hyperbolic neural network structures have been
proposed, they mainly focus on discriminative tasks, and generative models in
the hyperbolic space have scarcely been studied. In this work, we propose a
hyperbolic generative adversarial network (GAN) within the Lorentz model for
generating hyperbolic data. In …

arxiv generative adversarial network network