2 citations · 2 across the 1 of their papers we have counts for
5 papers
Distilling the Knowledge from Conditional Normalizing Flows
Dmitry Baranchuk, Vladimir Aliev, Artem Babenko
Normalizing flows are a powerful class of generative models demonstrating strong performance in several speech and vision problems. In contrast to other generative models, normaliz…
Free-Lunch Saliency via Attention in Atari Agents
Dmitry Nikulin, Anastasia Ianina, Vladimir Aliev +1
We propose a new approach to visualize saliency maps for deep neural network models and apply it to deep reinforcement learning agents trained on Atari environments. Our method add…
Learning State Representations in Complex Systems with Multimodal Data
Pavel Solovev, Vladimir Aliev, Pavel Ostyakov +7
Representation learning becomes especially important for complex systems with multimodal data sources such as cameras or sensors. Recent advances in reinforcement learning and opti…
Deep Learning Approaches for Understanding Simple Speech Commands
Roman A. Solovyev, Maxim Vakhrushev, Alexander Radionov +2
Automatic classification of sound commands is becoming increasingly important, especially for mobile and embedded devices. Many of these devices contain both cameras and microphone…
Label Denoising with Large Ensembles of Heterogeneous Neural Networks
Pavel Ostyakov, Elizaveta Logacheva, Roman Suvorov +4
Despite recent advances in computer vision based on various convolutional architectures, video understanding remains an important challenge. In this work, we present and discuss a…