Ignacio Segovia-Dominguez

Orcid: 0000-0003-0623-2331

According to our database1, Ignacio Segovia-Dominguez authored at least 24 papers between 2011 and 2024.

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Bibliography

2024
EMP: Effective Multidimensional Persistence for Graph Representation Learning.
CoRR, 2024

Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Seven open problems in applied combinatorics.
CoRR, 2023

2022
Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning on Health Fairness and Environmental Justice via Interactive Visualization.
Proceedings of the IEEE International Conference on Big Data, 2022

Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Using NASA Satellite Data Sources and Geometric Deep Learning to Uncover Hidden Patterns in COVID-19 Clinical Severity.
CoRR, 2021

Smart Vectorizations for Single and Multiparameter Persistence.
CoRR, 2021

Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Geospatial forecasting of COVID-19 spread and risk of reaching hospital capacity.
ACM SIGSPATIAL Special, 2020

Geometric probabilistic evolutionary algorithm.
Expert Syst. Appl., 2020

2015
An Estimation of Distribution Algorithm based on the Natural Gradient and the Boltzmann Distribution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Designing the Boltzmann Estimation of Multivariate Normal Distribution: Issues, goals and solutions.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

2014
A New EDA by a Gradient-Driven Density.
Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

A Boltzmann Multivariate Estimation of Distribution Algorithm for Continuous Optimization.
Proceedings of the ECTA 2014, 2014

2013
The Gaussian Polytree EDA with Copula Functions and Mutations.
Proceedings of the EVOLVE, 2013

Building multivariate density functions based on promising direction vectors.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2011
Global Optimization with the Gaussian Polytree EDA.
Proceedings of the Advances in Soft Computing, 2011

The gaussian polytree EDA for global optimization.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011


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