Yulia R. Gel

Orcid: 0000-0002-4500-6495

According to our database1, Yulia R. Gel authored at least 70 papers between 2007 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

SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

TopoGCL: Topological Graph Contrastive Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Seven open problems in applied combinatorics.
CoRR, 2023

H<sup>2</sup>-Nets: Hyper-hodge Convolutional Neural Networks for Time-Series Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Topological Graph Convolutional Networks Solutions for Power Distribution Grid Planning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Graph of Graphs: A New Knowledge Representation Mechanism for Graph Learning (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Topological Pooling on Graphs.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Blockchain networks: Data structures of Bitcoin, Monero, Zcash, Ethereum, Ripple, and Iota.
WIREs Data Mining Knowl. Discov., 2022

TopoAttn-Nets: Topological Attention in Graph Representation Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 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

Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT.
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

Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets.
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

TCN: Pioneering Topological-Based Convolutional Networks for Planetary Terrain Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

BScNets: Block Simplicial Complex Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
GraphBoot: Quantifying Uncertainty in Node Feature Learning on Large Networks.
IEEE Trans. Knowl. Data Eng., 2021

Depth-based classification for relational data with multiple attributes.
J. Multivar. Anal., 2021

Nonparametric Anomaly Detection on Time Series of Graphs.
J. Comput. Graph. Stat., 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

Topological Relational Learning on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Alphacore: Data Depth based Core Decomposition.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on 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

Data Science on Blockchains.
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

Defending against Backdoors in Federated Learning with Robust Learning Rate.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Topological Machine Learning Methods for Power System Responses to Contingencies.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

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

How to Not Get Caught When You Launder Money on Blockchain?
CoRR, 2020

A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico.
IEEE Access, 2020

Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of the Ethereum Graph?
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

BitcoinHeist: Topological Data Analysis for Ransomware Prediction on the Bitcoin Blockchain.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

LFGCN: Levitating over Graphs with Levy Flights.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Fusing data depth with complex networks: Community detection with prior information.
Comput. Stat. Data Anal., 2019

Harnessing the power of Topological Data Analysis to detect change points in time series.
CoRR, 2019

Unsupervised Space-Time Clustering using Persistent Homology.
CoRR, 2019

BitcoinHeist: Topological Data Analysis for Ransomware Detection on the Bitcoin Blockchain.
CoRR, 2019

ChainNet: Learning on Blockchain Graphs with Topological Features.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Deep Learning for Improved Agricultural Risk Management.
Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019

Assessing the Resilience of the Texas Power Grid Network.
Proceedings of the IEEE Data Science Workshop, 2019

2018
Snowboot: Bootstrap Methods for Network Inference.
R J., 2018

Deep Ensemble Classifiers and Peer Effects Analysis for Churn Forecasting in Retail Banking.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Forecasting Bitcoin Price with Graph Chainlets.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Attacklets: Modeling High Dimensionality in Real World Cyberattacks.
Proceedings of the 2018 IEEE International Conference on Intelligence and Security Informatics, 2018

Blockchain Data Analytics.
Proceedings of the IEEE International Conference on Data Mining, 2018

Role of Local Geometry in Robustness of Power Grid Networks.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

2017
Blockchain: A Graph Primer.
CoRR, 2017

CRAD: Clustering with Robust Autocuts and Depth.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Motif-based analysis of power grid robustness under attacks.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Intentional islanding of power grids with data depth.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016
Estimation of river and stream temperature trends under haphazard sampling.
Stat. Methods Appl., 2016

A local factor nonparametric test for trend synchronism in multiple time series.
J. Multivar. Anal., 2016

A distribution-free m-out-of-n bootstrap approach to testing symmetry about an unknown median.
Comput. Stat. Data Anal., 2016

Catching Social Butterflies: Identifying Influential Users of an Event-Based Social Networking Service.
Proceedings of the 2016 IEEE International Congress on Big Data, San Francisco, CA, USA, June 27, 2016

2013
A new surveillance and spatio-temporal visualization tool SIMID: SIMulation of Infectious Diseases using random networks and GIS.
Comput. Methods Programs Biomed., 2013

2010
Autoregressive frequency detection using Regularized Least Squares.
J. Multivar. Anal., 2010

Test of fit for a Laplace distribution against heavier tailed alternatives.
Comput. Stat. Data Anal., 2010

2007
Robust directed tests of normality against heavy-tailed alternatives.
Comput. Stat. Data Anal., 2007


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