The gaussian polytree EDA for global optimization. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre; Enrique Raúl Villa Diharce (GECCO (Companion), 2011)

Global Optimization with the Gaussian Polytree EDA. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre; Enrique Raúl Villa Diharce (MICAI (2), 2011)

Building multivariate density functions based on promising direction vectors. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre (IEEE Congress on Evolutionary Computation, 2013)

The Gaussian Polytree EDA with Copula Functions and Mutations. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre; Enrique Raúl Villa Diharce (EVOLVE, 2013)

A Boltzmann Multivariate Estimation of Distribution Algorithm for Continuous Optimization. - Ignacio Segovia-Dominguez; Sergio Ivvan Valdez; Arturo Hernández Aguirre (IJCCI (ECTA), 2014)

A New EDA by a Gradient-Driven Density. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre; Sergio Ivvan Valdez (PPSN, 2014)

Designing the Boltzmann Estimation of Multivariate Normal Distribution: Issues, goals and solutions. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre; Sergio Ivvan Valdez (CEC, 2015)

An Estimation of Distribution Algorithm based on the Natural Gradient and the Boltzmann Distribution. - Ignacio Segovia-Dominguez; Arturo Hernández Aguirre (GECCO, 2015)

Geometric probabilistic evolutionary algorithm. - Ignacio Segovia-Dominguez; Rafael Herrera Guzmán; Juan Pablo Serrano Rubio; Arturo Hernández Aguirre (Expert Syst. Appl., 2020)

Geospatial forecasting of COVID-19 spread and risk of reaching hospital capacity. - Georgiy V. Bobashev; Ignacio Segovia-Dominguez; Yulia R. Gel; James Rineer; Sarah Rhea; Hui Sui (ACM SIGSPATIAL Special, 2020)

Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting. - Yuzhou Chen; Ignacio Segovia-Dominguez; Yulia R. Gel (ICML, 2021)

Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning. - Ignacio Segovia-Dominguez; Huikyo Lee; Yuzhou Chen; Michael J. Garay; Krzysztof M. Gorski; Yulia R. Gel (KDD, 2021)

TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions. - Ignacio Segovia-Dominguez; Zhiwei Zhen; Rishabh Wagh; Huikyo Lee; Yulia R. Gel (PAKDD (1), 2021)

Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks. - Dorcas Ofori-Boateng; Ignacio Segovia-Dominguez; Cuneyt Gurcan Akcora; Murat Kantarcioglu; Yulia R. Gel (ECML/PKDD (1), 2021)

Smart Vectorizations for Single and Multiparameter Persistence. - Baris Coskunuzer; Cuneyt Gurcan Akcora; Ignacio Segovia-Dominguez; Zhiwei Zhen; Murat Kantarcioglu; Yulia R. Gel (CoRR, 2021)

Using NASA Satellite Data Sources and Geometric Deep Learning to Uncover Hidden Patterns in COVID-19 Clinical Severity. - Ignacio Segovia-Dominguez; Huikyo Lee; Zhiwei Zhen; Yuzhou Chen; Michael J. Garay; Daniel J. Crichton; Rishabh Wagh; Yulia R. Gel (CoRR, 2021)

Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance. - Tian Jiang; Meichen Huang; Ignacio Segovia-Dominguez; Nathaniel K. Newlands; Yulia R. Gel (AAAI, 2022)

Learning on Health Fairness and Environmental Justice via Interactive Visualization. - Abdullah al-Raihan Nayeem; Ignacio Segovia-Dominguez; Huikyo Lee; Dongyun Han; Yuzhou Chen; Zhiwei Zhen; Yulia R. Gel; Isaac Cho (IEEE Big Data, 2022)

TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting. - Yuzhou Chen; Ignacio Segovia-Dominguez; Baris Coskunuzer; Yulia R. Gel (ICLR, 2022)

ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery. - Andac Demir; Baris Coskunuzer; Yulia R. Gel; Ignacio Segovia-Dominguez; Yuzhou Chen; Bulent Kiziltan (NeurIPS, 2022)

Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning. - Zhiwei Zhen; Yuzhou Chen; Ignacio Segovia-Dominguez; Yulia R. Gel (PAKDD (2), 2022)

EMP: Effective Multidimensional Persistence for Graph Representation Learning. - Yuzhou Chen; Ignacio Segovia-Dominguez; Cuneyt Gurcan Akcora; Zhiwei Zhen; Murat Kantarcioglu; Yulia R. Gel; Baris Coskunuzer (LoG, 2023)

Seven open problems in applied combinatorics. - Sinan G. Aksoy; Ryan S. Bennink; Yuzhou Chen; José Frías; Yulia R. Gel; Bill Kay; Uwe Naumann; Carlos Ortiz Marrero; Anthony V. Petyuk; Sandip Roy 002; Ignacio Segovia-Dominguez; Nate Veldt; et al. (CoRR, 2023)

Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence. - Baris Coskunuzer; Ignacio Segovia-Dominguez; Yuzhou Chen; Yulia R. Gel (AAAI, 2024)