20 citations · 21 across the 2 of their papers we have counts for
3 papers
Optimizing the Neural Architecture of Reinforcement Learning Agents
N. Mazyavkina, S. Moustafa, I. Trofimov +1
Reinforcement learning (RL) enjoyed significant progress over the last years. One of the most important steps forward was the wide application of neural networks. However, architec…
Perceptual deep depth super-resolution
Oleg Voynov, Alexey Artemov, Vage Egiazarian +4
RGBD images, combining high-resolution color and lower-resolution depth from various types of depth sensors, are increasingly common. One can significantly improve the resolution o…
Latent Convolutional Models
ShahRukh Athar, Evgeny Burnaev, Victor Lempitsky
We present a new latent model of natural images that can be learned on large-scale datasets. The learning process provides a latent embedding for every image in the training datase…