3 citations · 3 across the 2 of their papers we have counts for
4 papers
Generating new pictures in complex datasets with a simple neural network
Galin Georgiev
We introduce a version of a variational auto-encoder (VAE), which can generate good perturbations of images, when trained on a complex dataset (in our experiments, CIFAR-10). The n…
Linear Algebra and Duality of Neural Networks
Galin Georgiev
Bases, mappings, projections and metrics, natural for Neural network training, are introduced. Graph-theoretical interpretation is offered. Non-Gaussianity naturally emerges, even…
Symmetries and control in generative neural nets
Galin Georgiev
We study generative nets which can control and modify observations, after being trained on real-life datasets. In order to zoom-in on an object, some spatial, color and other attri…
Towards universal neural nets: Gibbs machines and ACE
Galin Georgiev
We study from a physics viewpoint a class of generative neural nets, Gibbs machines, designed for gradual learning. While including variational auto-encoders, they offer a broader…