Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kochurov, Max"'
Recently there was an increasing interest in applications of graph neural networks in non-Euclidean geometry; however, are non-Euclidean representations always useful for graph learning tasks? For different problems such as node classification and li
Externí odkaz:
http://arxiv.org/abs/2007.07698
Geoopt is a research-oriented modular open-source package for Riemannian Optimization in PyTorch. The core of Geoopt is a standard Manifold interface that allows for the generic implementation of optimization algorithms. Geoopt supports basic Riemann
Externí odkaz:
http://arxiv.org/abs/2005.02819
Autor:
Alanov, Aibek, Kochurov, Max, Volkhonskiy, Denis, Yashkov, Daniil, Burnaev, Evgeny, Vetrov, Dmitry
We propose a novel multi-texture synthesis model based on generative adversarial networks (GANs) with a user-controllable mechanism. The user control ability allows to explicitly specify the texture which should be generated by the model. This proper
Externí odkaz:
http://arxiv.org/abs/1904.04751
We propose a novel autoencoding model called Pairwise Augmented GANs. We train a generator and an encoder jointly and in an adversarial manner. The generator network learns to sample realistic objects. In turn, the encoder network at the same time is
Externí odkaz:
http://arxiv.org/abs/1810.04920
Autor:
Kochurov, Max, Garipov, Timur, Podoprikhin, Dmitry, Molchanov, Dmitry, Ashukha, Arsenii, Vetrov, Dmitry
In industrial machine learning pipelines, data often arrive in parts. Particularly in the case of deep neural networks, it may be too expensive to train the model from scratch each time, so one would rather use a previously learned model and the new
Externí odkaz:
http://arxiv.org/abs/1802.07329