Hadi Meidani

CoRR, 2024

Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment.

[BibT_eX]

[DOI]

CoRR, 2024

Physics-Informed Geometry-Aware Neural Operator.

[BibT_eX]

[DOI]

CoRR, 2024

Physics-informed Mesh-independent Deep Compositional Operator Network.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Heterogeneous Graph Neural Networks for Data-driven Traffic Assignment.

[BibT_eX]

[DOI]

CoRR, 2023

Attention-based Spatial-Temporal Graph Neural ODE for Traffic Prediction.

[BibT_eX]

[DOI]

Jane MacFarlane

CoRR, 2023

GNN-based physics solver for time-independent PDEs.

[BibT_eX]

[DOI]

CoRR, 2023

Graph Pyramid Autoformer for Long- Term Traffic Forecasting.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2023

Optimizing Seismic Retrofit of Bridges: Integrating Efficient Graph Neural Network Surrogates and Transportation Equity.

[BibT_eX]

[DOI]

Proceedings of Cyber-Physical Systems and Internet of Things Week 2023, 2023

2022

Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram.

[BibT_eX]

[DOI]

Amir Kazemi

CoRR, 2022

FO-PINNs: A First-Order formulation for Physics Informed Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Graph Neural Network Surrogate for seismic reliability analysis of highway bridge system.

[BibT_eX]

[DOI]

CoRR, 2022

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting.

[BibT_eX]

[DOI]

CoRR, 2022

PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Robust Topology Optimization Using Variational Autoencoders.

[BibT_eX]

[DOI]

Vahid Keshavarzzadeh

CoRR, 2021

Efficient training of physics-informed neural networks via importance sampling.

[BibT_eX]

[DOI]

Comput. Aided Civ. Infrastructure Eng., 2021

IGANI: Iterative Generative Adversarial Networks for Imputation With Application to Traffic Data.

[BibT_eX]

[DOI]

Amir Kazemi

IEEE Access, 2021

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

[BibT_eX]

[DOI]

IEEE Access, 2021

2020

Efficient Collection of Connected Vehicles Data With Precision Guarantees.

[BibT_eX]

[DOI]

IEEE Trans. Intell. Transp. Syst., 2020

Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis.

[BibT_eX]

[DOI]

J. Comput. Inf. Sci. Eng., 2020

IGANI: Iterative Generative Adversarial Networks for Imputation Applied to Prediction of Traffic Data.

[BibT_eX]

[DOI]

Amir Kazemi

CoRR, 2020

Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

IEEE Access, 2020

2018

Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data.

[BibT_eX]

[DOI]

Xu Wu

Tomasz Kozlowski

Reliab. Eng. Syst. Saf., 2018

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

[BibT_eX]

[DOI]

J. Comput. Phys., 2018

Physics-Informed Regularization of Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

A Deep Neural Network Surrogate for High-Dimensional Random Partial Differential Equations.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks.

[BibT_eX]

[DOI]

Comput. Aided Civ. Infrastructure Eng., 2018

A Recursive Data-driven Model for Traffic Flow Predictions for Locations with Faulty Sensors.

[BibT_eX]

[DOI]

Shiyu Wang

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2017

Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks.

[BibT_eX]

[DOI]