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Early prediction of response to palliative chemotherapy in patients with stage-IV gastric and esophageal cancer

BMC cancer, 2023-09, Vol.23 (1), p.1-910, Article 910

2023

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Smart-Meter Big Data for Load Forecasting: An Alternative Approach to Clustering

IEEE access, 2022, Vol.10, p.8377-8387

2022

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HEvOD: A database of hurricane evacuation orders in the United States

Scientific data, 2024-03, Vol.11 (1), p.270-270, Article 270

2024

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A Data-Driven Multi-Fidelity Approach for Traffic State Estimation Using Data From Multiple Sources

IEEE access, 2021, Vol.9, p.78128-78137

2021

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Fast Probabilistic Voltage Control for Distribution Networks With Distributed Generation Using Polynomial Surrogates

IEEE access, 2020, Vol.8, p.73536-73546

2020

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Survival analysis at multiple scales for the modeling of track geometry deterioration

Proceedings of the Institution of Mechanical Engineers. Part F, Journal of rail and rapid transit, 2018-03, Vol.232 (3), p.842-850

2018

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Bottom-up forecasting: Applications and limitations in load forecasting using smart-meter data

Data-Centric Engineering (Online), 2023-01, Vol.4, Article e14

2023

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A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions

Journal of computational physics, 2018-10, Vol.371, p.137-151

2018

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Divide and conquer: An incremental sparsity promoting compressive sampling approach for polynomial chaos expansions

Computer methods in applied mechanics and engineering, 2017-05, Vol.318, p.937-956

2017

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A preconditioning approach for improved estimation of sparse polynomial chaos expansions

Computer methods in applied mechanics and engineering, 2018-12, Vol.342, p.474-489, Article 474

2018

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Efficient Collection of Connected Vehicles Data With Precision Guarantees

IEEE transactions on intelligent transportation systems, 2020-11, Vol.21 (11), p.4637-4645

2020

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A multi-fidelity polynomial chaos-greedy Kaczmarz approach for resource-efficient uncertainty quantification on limited budget

Computer methods in applied mechanics and engineering, 2022-02, Vol.389, p.114290, Article 114290

2022

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Predicting Near-Term Train Schedule Performance and Delay Using Bi-Level Random Forests

Transportation research record, 2019-05, Vol.2673 (5), p.564-573

2019

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MULTI-FIDELITY MACHINE LEARNING FOR UNCERTAINTY QUANTIFICATION AND OPTIMIZATION

Journal of machine learning for modeling and computing (Print), 2024, Vol.5 (4), p.77-94

2024

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Multifidelity graph neural networks for efficient and accurate mesh‐based partial differential equations surrogate modeling

Computer-aided civil and infrastructure engineering, 2024-07

2024

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Multi-Fidelity Physics-Informed Generative Adversarial Network for Solving Partial Differential Equations

Journal of computing and information science in engineering, 2024-11, Vol.24 (11)

2024

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IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH

International journal for uncertainty quantification, 2024, Vol.14 (1), p.1-18

2024

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Spatio-temporal graph attention network-based detection of FDIA from smart meter data at geographically hierarchical levels

Electric power systems research, 2025-01, Vol.238, p.111149, Article 111149

2025

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Multi-fidelity graph neural networks for efficient power flow analysis under high-dimensional demand and renewable generation uncertainty

Electric power systems research, 2024-12, Vol.237, p.111014, Article 111014

2024

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HYBRID CHANCE-CONSTRAINED OPTIMAL POWER FLOW UNDER LOAD AND RENEWABLE GENERATION UNCERTAINTY USING ENHANCED MULTI-FIDELITY GRAPH NEURAL NETWORKS

Journal of machine learning for modeling and computing (Print), 2024, Vol.5 (4), p.53-76

2024

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Hurricane-induced power outage risk under climate change is primarily driven by the uncertainty in projections of future hurricane frequency

Scientific reports, 2020-09, Vol.10 (1), Article 15270

2020

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DESIGN OF EXPERIMENTS VIA MULTI-FIDELITY SURROGATES AND STATISTICAL SENSITIVITY MEASURES

Journal of machine learning for modeling and computing (Print), 2024, Vol.5 (4), p.95-121

2024

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Using Empirical Data to Find the Best Measure of Travel Time Reliability

Transportation research record, 2015-01, Vol.2530 (1), p.93-100

2015

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The impact of HOT lanes on carpools

Research in transportation economics, 2014-06, Vol.44, p.43-51

2014

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Examining Potential Travel Time Savings Benefits Due to Toll Rates That Vary by Lane

Journal of transportation technologies, 2014, Vol.4 (3), p.267-276

2014

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Early prediction of response to palliative chemotherapy in patients with stage-IV gastric and esophageal cancer

Smart-Meter Big Data for Load Forecasting: An Alternative Approach to Clustering

HEvOD: A database of hurricane evacuation orders in the United States

A Data-Driven Multi-Fidelity Approach for Traffic State Estimation Using Data From Multiple Sources

Fast Probabilistic Voltage Control for Distribution Networks With Distributed Generation Using Polynomial Surrogates

Survival analysis at multiple scales for the modeling of track geometry deterioration

Bottom-up forecasting: Applications and limitations in load forecasting using smart-meter data

A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions

Divide and conquer: An incremental sparsity promoting compressive sampling approach for polynomial chaos expansions

A preconditioning approach for improved estimation of sparse polynomial chaos expansions

Efficient Collection of Connected Vehicles Data With Precision Guarantees

A multi-fidelity polynomial chaos-greedy Kaczmarz approach for resource-efficient uncertainty quantification on limited budget

Predicting Near-Term Train Schedule Performance and Delay Using Bi-Level Random Forests

MULTI-FIDELITY MACHINE LEARNING FOR UNCERTAINTY QUANTIFICATION AND OPTIMIZATION

Multifidelity graph neural networks for efficient and accurate mesh‐based partial differential equations surrogate modeling

Multi-Fidelity Physics-Informed Generative Adversarial Network for Solving Partial Differential Equations

IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH

Spatio-temporal graph attention network-based detection of FDIA from smart meter data at geographically hierarchical levels

Multi-fidelity graph neural networks for efficient power flow analysis under high-dimensional demand and renewable generation uncertainty

HYBRID CHANCE-CONSTRAINED OPTIMAL POWER FLOW UNDER LOAD AND RENEWABLE GENERATION UNCERTAINTY USING ENHANCED MULTI-FIDELITY GRAPH NEURAL NETWORKS

Hurricane-induced power outage risk under climate change is primarily driven by the uncertainty in projections of future hurricane frequency

DESIGN OF EXPERIMENTS VIA MULTI-FIDELITY SURROGATES AND STATISTICAL SENSITIVITY MEASURES

Using Empirical Data to Find the Best Measure of Travel Time Reliability

The impact of HOT lanes on carpools

Examining Potential Travel Time Savings Benefits Due to Toll Rates That Vary by Lane

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