24 citations · 31 across the 8 of their papers we have counts for
8 papers
Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials
Federico Ottomano, John Y. Goulermas, Vladimir Gusev +14
Machine Learning (ML) has offered innovative perspectives for accelerating the discovery of new functional materials, leveraging the increasing availability of material databases.…
Cluster Exploration using Informative Manifold Projections
Stavros Gerolymatos, Xenophon Evangelopoulos, Vladimir Gusev +1
Dimensionality reduction (DR) is one of the key tools for the visual exploration of high-dimensional data and uncovering its cluster structure in two- or three-dimensional spaces.…
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous Variables
Penglei Gao, Xi Yang, Rui Zhang +3
While exogenous variables have a major impact on performance improvement in time series analysis, inter-series correlation and time dependence among them are rarely considered in t…
Densest plane group packings of regular polygons
Miloslav Torda, John Y. Goulermas, Vitaliy Kurlin +1
Packings of regular convex polygons (-gons) that are sufficiently dense have been studied extensively in the context of modeling physical and biological systems as well as discr…
Process Mining Algorithm for Online Intrusion Detection System
Yinzheng Zhong, John Y. Goulermas, Alexei Lisitsa
In this paper, we consider the applications of process mining in intrusion detection. We propose a novel process mining inspired algorithm to be used to preprocess data in intrusio…
Entropic trust region for densest crystallographic symmetry group packings
Miloslav Torda, John Y. Goulermas, Roland Púček +1
Molecular crystal structure prediction (CSP) seeks the most stable periodic structure given the chemical composition of a molecule and pressure-temperature conditions. Modern CSP s…
Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
Mingjie Sun, Jimin Xiao, Eng Gee Lim +2
In this paper, we are tackling the weakly-supervised referring expression grounding task, for the localization of a referent object in an image according to a query sentence, where…
Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series Prediction
Penglei Gao, Xi Yang, Rui Zhang +1
We propose a continuous neural network architecture, termed Explainable Tensorized Neural Ordinary Differential Equations (ETN-ODE), for multi-step time series prediction at arbitr…