4 papers
Persistence-Augmented Neural Networks
Elena Xinyi Wang, Arnur Nigmetov, Dmitriy Morozov
Topological Data Analysis (TDA) provides tools to describe the shape of data, but integrating topological features into deep learning pipelines remains challenging, especially when…
Topological potentials guiding protein self-assembly
Ivan Spirandelli, Arnur Nigmetov, Dmitriy Morozov +1
The simulated self-assembly of molecular building blocks into functional complexes is a key area of study in computational biology and materials science. Self-assembly simulations…
Distributed Computation of Persistent Cohomology
Arnur Nigmetov, Dmitriy Morozov
Persistent (co)homology is a central construction in topological data analysis, where it is used to quantify prominence of features in data to produce stable descriptors suitable f…
Wilkins: HPC In Situ Workflows Made Easy
Orcun Yildiz, Dmitriy Morozov, Arnur Nigmetov +2
In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however,…