2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
Learning Topology-Preserving Data Representations
Ilya Trofimov, Daniil Cherniavskii, Eduard Tulchinskii +3
We propose a method for learning topology-preserving data representations (dimensionality reduction). The method aims to provide topological similarity between the data manifold an…
cs.LG2022
Transfer learning for ensembles: reducing computation time and keeping the diversity
Ilya Shashkov, Nikita Balabin, Evgeny Burnaev +1
Transferring a deep neural network trained on one problem to another requires only a small amount of data and little additional computation time. The same behaviour holds for ensem…