3 citations · 5 across the 6 of their papers we have counts for
6 papers
Open-World Class Discovery with Kernel Networks
Zifeng Wang, Batool Salehi, Andrey Gritsenko +3
We study an Open-World Class Discovery problem in which, given labeled training samples from old classes, we need to discover new classes from unlabeled test samples. There are two…
Incremental ELMVIS for unsupervised learning
Anton Akusok, Emil Eirola, Yoan Miche +5
An incremental version of the ELMVIS+ method is proposed in this paper. It iteratively selects a few best fitting data samples from a large pool, and adds them to the model. The me…
Topological Brain Network Distances
Moo K. Chung, Hyekyoung Lee, Andrey Gritsenko +4
Existing brain network distances are often based on matrix norms. The element-wise differences in the existing matrix norms may fail to capture underlying topological differences.…
Automatic Identification of Twin Zygosity in Resting-State Functional MRI
Andrey Gritsenko, Martin A. Lindquist, Gregory R. Kirk +1
A key strength of twin studies arises from the fact that there are two types of twins, monozygotic and dizygotic, that share differing amounts of genetic information. Accurate diff…
Embedded Spectral Descriptors: Learning the point-wise correspondence metric via Siamese neural networks
Zhiyu Sun, Yusen He, Andrey Gritsenko +2
A robust and informative local shape descriptor plays an important role in mesh registration. In this regard, spectral descriptors that are based on the spectrum of the Laplace-Bel…
A Workflow-Forecast Approach To The Task Scheduling Problem In Distributed Computing Systems
Andrey Gritsenko
The aim of this paper is to provide a description of deep-learning-based scheduling approach for academic-purpose high-performance computing systems. The share of academic-purpose…