Christian Moya

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 28

Top Topics

Dynamic Response

Top Venues

IET Cyper-Phys. Syst.: Theory & Appl.

Publications

Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks. CoRR (2024)
Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. AISTATS (2024)
Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. CoRR (2024)
Guang Lin, Christian Moya, Zecheng Zhang
B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD. J. Comput. Phys. 473 (2023)
Christian Moya, Guang Lin, Tianqiao Zhao, Meng Yue
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators. CoRR (2023)
Amirhossein Mollaali, Izzet Sahin, Iqrar Raza, Christian Moya, Guillermo Paniagua, Guang Lin
A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients. CoRR (2023)
Christian Moya, Guang Lin
DAE-PINN: a physics-informed neural network model for simulating differential algebraic equations with application to power networks. Neural Comput. Appl. 35 (5) (2023)
Christian Moya, Shiqi Zhang, Guang Lin, Meng Yue
DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid's post-fault trajectories. Neurocomputing 535 (2023)
Zhihao Kong, Amirhossein Mollaali, Christian Moya, Na Lu, Guang Lin
B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions. CoRR (2023)
Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR (2023)
Guang Lin, Christian Moya, Zecheng Zhang
Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks. Eng. Appl. Artif. Intell. 125 (2023)
Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems. IEEE Syst. J. 17 (3) (2023)
Izzet Sahin, Christian Moya, Amirhossein Mollaali, Guang Lin, Guillermo Paniagua
Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles. CoRR (2023)
Christian Moya, Guang Lin
Bayesian, Multifidelity Operator Learning for Complex Engineering Systems-A Position Paper. J. Comput. Inf. Sci. Eng. 23 (6) (2023)
Binghang Lu, Christian Moya, Guang Lin
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training. Algorithms 16 (4) (2023)
Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR (2023)
Christian Moya, Guang Lin
Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks. Algorithms 15 (9) (2022)
Guang Li, Christian Moya, Zecheng Zhang
On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks. CoRR (2022)
Christian Moya, Shiqi Zhang, Meng Yue, Guang Lin
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories. CoRR (2022)
Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems. CoRR (2022)
Christian Moya, Guang Lin
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks. CoRR (2021)
Guang Lin, Christian Moya, Zecheng Zhang
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs. CoRR (2021)
Jiankang Wang, Gonzalo E. Constante, Christian Moya, Junho Hong
Semantic analysis framework for protecting the power grid against monitoring-control attacks. IET Cyper-Phys. Syst.: Theory & Appl. 5 (1) (2020)
Gonzalo E. Constante, Christian Moya, Jiankang Wang
Semantic-Based Detection Architectures Against Monitoring-Control Attacks in Power Grids. SmartGridComm (2019)
Christian Moya, Jiankang Wang
Developing correlation indices to identify coordinated cyber-attacks on power grids. IET Cyper-Phys. Syst.: Theory & Appl. 3 (4) (2019)
Christian Moya, Junho Hong, Jiankang Wang
Application of Correlation Indices on Intrusion Detection Systems: Protecting the Power Grid Against Coordinated Attacks. CoRR (2018)
Christian Moya, Jiankang Wang
Developing a Correlation Index to Identify Coordinated Cyber-Attacks to Power Grids. CoRR (2017)
Christian Moya, Jiankang Wang
Cyber-Attacks to Voltage Control Applications via Wide Area Monitoring, Protection and Control System. SPSR-SG@CPSWeek (2017)
Christian Moya, Wei Zhang, Jianming Lian, Karanjit Kalsi
A hierarchical framework for demand-side frequency control. ACC (2014)