65 citations · 127 across the 13 of their papers we have counts for
3 papers · 1 filter
Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds
Vage Egiazarian, Savva Ignatyev, Alexey Artemov +5
Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, engineering, and design. Despit…
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs
Denis Mazur, Vage Egiazarian, Stanislav Morozov +1
Learning useful representations is a key ingredient to the success of modern machine learning. Currently, representation learning mostly relies on embedding data into Euclidean spa…
Wasserstein-2 Generative Networks
Alexander Korotin, Vage Egiazarian, Arip Asadulaev +2
We propose a novel end-to-end non-minimax algorithm for training optimal transport mappings for the quadratic cost (Wasserstein-2 distance). The algorithm uses input convex neural…