Yulia Gel
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Yulia Gelmathematics Degrees
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Mathematics
Yulia Gel's Degrees
- PhD Mathematics Stanford University
- Bachelors Mathematics University of California, Berkeley
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Why Is Yulia Gel Influential?
(Suggest an Edit or Addition)According to Wikipedia, Yulia R. Gel is a professor in the Department of Mathematical Sciences at the University of Texas at Dallas and an adjunct professor in the Department of Statistics and Actuarial Science of the University of Waterloo.
Yulia Gel's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- The impact of Levene’s test of equality of variances on statistical theory and practice (2009) (390)
- Influenza Forecasting with Google Flu Trends (2013) (312)
- A robust modification of the Jarque–Bera test of normality (2008) (135)
- lawstat: An R Package for Law, Public Policy and Biostatistics (2008) (134)
- Calibrated Probabilistic Mesoscale Weather Field Forecasting (2004) (93)
- Forecasting influenza in Hong Kong with Google search queries and statistical model fusion (2017) (86)
- Robust directed tests of normality against heavy-tailed alternatives (2007) (77)
- BitcoinHeist: Topological Data Analysis for Ransomware Detection on the Bitcoin Blockchain (2019) (74)
- A New Test of Symmetry about an Unknown Median (2006) (64)
- Forecasting Bitcoin Price with Graph Chainlets (2018) (63)
- Nonparametric short-term probabilistic forecasting for solar radiation (2016) (56)
- Bootstrap-based tests for trends in hydrological time series, with application to ice phenology data (2011) (48)
- What network motifs tell us about resilience and reliability of complex networks (2019) (48)
- Banded regularization of autocovariance matrices in application to parameter estimation and forecasting of time series (2011) (46)
- Bitcoin Risk Modeling With Blockchain Graphs (2018) (41)
- Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes (2011) (40)
- Blockchain: A Graph Primer (2017) (34)
- ChainNet: Learning on Blockchain Graphs with Topological Features (2019) (33)
- Forecasting demand for health services: Development of a publicly available toolbox (2015) (32)
- Defending Against Backdoors in Federated Learning with Robust Learning Rate (2020) (31)
- Estimation of ice thickness on large northern lakes from AMSR-E brightness temperature measurements (2014) (30)
- Combination of Levene-type tests and a finite-intersection method for testing equality of variances against ordered alternatives (2010) (29)
- Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting (2021) (27)
- Blockchain Data Analytics (2018) (25)
- Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph (2019) (24)
- A new surveillance and spatio-temporal visualization tool SIMID: SIMulation of Infectious Diseases using random networks and GIS (2013) (24)
- On detecting non‐monotonic trends in environmental time series: a fusion of local regression and bootstrap (2013) (21)
- Insurance risk assessment in the face of climate change: Integrating data science and statistics (2019) (21)
- A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico (2020) (19)
- On the role of local blockchain network features in cryptocurrency price formation (2020) (19)
- A computational method for computing an Alzheimer's disease progression score; experiments and validation with the ADNI data set (2015) (19)
- Topological clustering of multilayer networks (2021) (17)
- Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA. (2019) (17)
- Comparative Analysis of the Local Observation-Based (LOB) Method and the Nonparametric Regression-Based Method for Gridded Bias Correction in Mesoscale Weather Forecasting (2007) (16)
- Using the bootstrap for statistical inference on random graphs (2014) (16)
- Women in Statistics (2017) (15)
- A hybrid approach for transmission grid resilience assessment using reliability metrics and power system local network topology (2020) (15)
- Bootstrap quantification of estimation uncertainties in network degree distributions (2017) (15)
- The Importance of Checking the Assumptions Underlying Statistical Analysis: Graphical Methods for Assessing Normality (2005) (14)
- Pan-Arctic linkages between snow accumulation and growing-season air temperature, soil moisture and vegetation (2013) (14)
- Robust Lagrange multiplier test for detecting ARCH/GARCH effect using permutation and bootstrap (2012) (13)
- Test of fit for a Laplace distribution against heavier tailed alternatives (2010) (13)
- Strong consistency of the regularized least-squares estimates of infinite autoregressive models (2007) (12)
- Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks (2021) (12)
- Political rhetoric through the lens of non‐parametric statistics: are our legislators that different? (2018) (12)
- Snowboot: Bootstrap Methods for Network Inference (2019) (11)
- Blockchain analytics for intraday financial risk modeling (2019) (11)
- Motif-based analysis of power grid robustness under attacks (2017) (11)
- Topological Relational Learning on Graphs (2021) (11)
- Harnessing the power of topological data analysis to detect change points (2019) (11)
- Unsupervised space–time clustering using persistent homology (2018) (10)
- Deep Learning at the Interface of Agricultural Insurance Risk and Spatio-Temporal Uncertainty in Weather Extremes (2019) (10)
- TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions (2021) (10)
- Geospatial forecasting of COVID-19 spread and risk of reaching hospital capacity (2020) (10)
- Tools for Biostatistics, Public Policy, and Law [R package lawstat version 3.4] (2020) (10)
- Can we weather proof our insurance? (2017) (9)
- Nonparametric Anomaly Detection on Time Series of Graphs (2019) (9)
- Estimation of river and stream temperature trends under haphazard sampling (2016) (9)
- Blockchain networks: Data structures of Bitcoin, Monero, Zcash, Ethereum, Ripple, and Iota (2021) (9)
- ROLE OF LOCAL GEOMETRY IN ROBUSTNESS OF POWER GRID NETWORKS (2018) (9)
- TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting (2022) (8)
- Deep Ensemble Classifiers and Peer Effects Analysis for Churn Forecasting in Retail Banking (2018) (7)
- Deep Learning for Improved Agricultural Risk Management (2019) (7)
- Fusing data depth with complex networks: Community detection with prior information (2019) (7)
- Evaluating the Impact of Climate Change on Dynamics of House Insurance Claims (2015) (7)
- Fast Community Detection in Complex Networks with a K -Depths Classifier (2017) (7)
- A distribution-free m-out-of-n bootstrap approach to testing symmetry about an unknown median (2016) (7)
- A local factor nonparametric test for trend synchronism in multiple time series (2016) (7)
- Identification of an unstable ARMA equation (2001) (7)
- BScNets: Block Simplicial Complex Neural Networks (2021) (6)
- Riding down the Bay: Space‐time clustering of ecological trends (2018) (6)
- Topological Machine Learning Methods for Power System Responses to Contingencies (2021) (6)
- LFGCN: Levitating over Graphs with Levy Flights (2020) (6)
- Autoregressive frequency detection using Regularized Least Squares (2010) (6)
- Ensemble forecasting of the Zika space‐time spread with topological data analysis (2020) (6)
- A conversation about implicit bias (2016) (6)
- Influenza Forecasting with Google Flu Trends (2013) (5)
- Reconfiguring Unbalanced Distribution Networks using Reinforcement Learning over Graphs (2022) (5)
- The effect of dependence between observations on the proper interpretation of statistical evidence (2008) (5)
- Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning (2021) (5)
- Leadership and Women in Statistics (2015) (5)
- Developing and Assessing E-Learning Techniques for Teaching Forecasting (2014) (5)
- Multilevel Random Slope Approach and Nonparametric Inference for River Temperature, Under Haphazard Sampling (2015) (5)
- Community detection in complex networks: From statistical foundations to data science applications (2021) (4)
- CRAD: Clustering with Robust Autocuts and Depth (2017) (4)
- How to Not Get Caught When You Launder Money on Blockchain? (2020) (3)
- A Sieve Bootstrap Two-Sample t-Test Under Serial Correlation (2011) (3)
- Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance (2022) (3)
- Intentional islanding of power grids with data depth (2017) (3)
- Evaluating Climate Change Impacts (2020) (3)
- Catching uncertainty of wind: A blend of sieve bootstrap and regime switching models for probabilistic short-term forecasting of wind speed (2016) (3)
- Depth-based classification for relational data with multiple attributes (2021) (3)
- Application of Topological Data Analysis to Multi-Resolution Matching of Aerosol Optical Depth Maps (2021) (2)
- Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting (2022) (2)
- Convergence analysis of the least-squares estimates for infinte AR models (2002) (2)
- Speaking out or speaking in? Changes in political rhetoric over time (2020) (2)
- Alphacore: Data Depth based Core Decomposition (2021) (2)
- Data Science on Blockchains (2021) (2)
- Combining Global and Local Grid-Based Bias Correction for Mesoscale Numerical Weather Prediction Models (2003) (2)
- GraphBoot: Quantifying Uncertainty in Node Feature Learning on Large Networks (2021) (2)
- Assessing the Resilience of the Texas Power Grid Network (2019) (2)
- Fast Patchwork Bootstrap for Quantifying Estimation Uncertainties in Sparse Random Networks (2016) (2)
- Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning (2021) (1)
- Fractional Graph Convolutional Networks (FGCN) for Semi-Supervised Learning (2019) (1)
- Testing for local covariate trend effects in volatility models (2020) (1)
- Catching Social Butterflies: Identifying Influential Users of an Event-Based Social Networking Service (2016) (1)
- Convergence of the least-squares method with a polynomial regularizer for the infinite-dimensional autoregression equation (2005) (1)
- Attacklets: Modeling High Dimensionality in Real World Cyberattacks (2018) (1)
- ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery (2022) (1)
- Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains (2022) (1)
- Regime Shift Analysis of Lake Baikal Freeze-up and Break-up Dates, and Ice Cover Duration (2009) (1)
- Smart Vectorizations for Single and Multiparameter Persistence (2021) (1)
- Regularized Autoregressive Multiple Frequency Estimation (2011) (1)
- Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning (2022) (1)
- Discussion of “High-dimensional autocovariance matrices and optimal linear prediction” (2015) (1)
- Alphacore (2021) (0)
- Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT (2022) (0)
- Climate Change, Cryosphere, and Atmospheric Chemistry (2013) (0)
- Bootstrap quantification of estimation uncertainties in network degree distributions (2017) (0)
- TopoAttn-Nets: Topological Attention in Graph Representation Learning (2022) (0)
- Levene's Family of Tests for Equality of Variances: historical perspective, impact and modiflcations (1960) (0)
- 2-14-2013 Influenza Forecasting with Google Flu Trends (2017) (0)
- EXTENDING LKN CLIMATE REGIONALIZATION WITH SPATIAL REGULARIZATION: AN APPLICATION TO EPIDEMIOLOGICAL RESEARCH (2016) (0)
- Editorial of Special Issue on Climate and Environment (2019) (0)
- A V ISION FOR THE D EVELOPMENT OF B ENCHMARKS TO B RIDGE G EOSCIENCE AND D ATA S CIENCE (2017) (0)
- Quantifying the impact of Covid-19 on stock market: An analysis from multi-source information (2020) (0)
- Convergence of the least-squares method with a polynomial regularizer for the infinite-dimensional autoregression equation (2005) (0)
- Estimation of river and stream temperature trends under haphazard sampling (2015) (0)
- Recent Advances and Trends in Time Series Analysis: Nonlinear Time Series, High Dimensional Inference and Beyond (2014) (0)
- Effective Collaboration Models for Statisticians and Public Health Departments (2015) (0)
- Conversations with Gábor J. Székely (2023) (0)
- Probabilistic forecasts of wind speed using the bootstrapped Markov regime switching model (2010) (0)
- Deep learning for satellite data-driven assessment and forecasting of particulate pollution over South Korea (2018) (0)
- Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction (2023) (0)
- Modeling of the spatial covariance structure of the brain using variograms with a non-Euclidean metric (2004) (0)
- Change‐point methods for environmental monitoring and assessment (2019) (0)
- Building Bridges Between Geoscience and Data Science through Benchmark Data Sets (2017) (0)
- CENTRAL GERMANY PRECIPITATION (2015) (0)
- Development of ice thickness retrieval algorithms for large northern lakes from AMSR-E brightness temperature measurements (2010) (0)
- Seven open problems in applied combinatorics (2023) (0)
- The linear model identification of stationary time series using its realization (1998) (0)
- Practical Suggestions for Developing as an Academic Leader (2015) (0)
- TCN: Pioneering Topological-Based Convolutional Networks for Planetary Terrain Learning (2022) (0)
- ATD 2020 Workshop Monday , 11 / 09 / 2020 (2020) (0)
- Learning on Health Fairness and Environmental Justice via Interactive Visualization (2022) (0)
- Using NASA Satellite Data Sources and Geometric Deep Learning to Uncover Hidden Patterns in COVID-19 Clinical Severity (2021) (0)
- Topological Pooling on Graphs (2023) (0)
- Professional Organization Membership (2015) (0)
- Learning Power Grid Outages with Higher-Order Topological Neural Networks (2023) (0)
- Modeling Weather-induced Home Insurance Risks with Support Vector Machine Regression (2021) (0)
- Rejoinder (2004) (0)
- Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets (2022) (0)
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