Christian Moya

38 papers A 1C 1Journal 34Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning. J. Comput. Phys. Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2026	J	`jnl`	pADAM: A Plug-and-Play All-in-One Diffusion Architecture for Multi-Physics Learning. CoRR Amirhossein Mollaali, Bongseok Kim, Christian Moya, Guang Lin
2025	J	`jnl`	A self-adaptive energy-based learning rate for stochastic gradient descent via Vector Auxiliary Variable method. Eng. Appl. Artif. Intell. Jiahao Zhang, Christian Moya, Guang Lin
2025	J	`jnl`	Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators. Neural Networks Amirhossein Mollaali, Gabriel Zufferey, Gonzalo Constante-Flores, Christian Moya, Can Li, Meng Yue, Guang Lin
2025	J	`jnl`	FPINN-deeponet: A physics-informed operator learning framework for multi-term time-fractional mixed diffusion-wave equations. J. Comput. Phys. Binghang Lu, Zhaopeng Hao, Christian Moya, Guang Lin
2024	A	`conf`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. AISTATS Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. CoRR Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method. CoRR Jiahao Zhang, Christian Moya, Guang Lin
2024	J	`jnl`	Bayesian Deep Operator Learning for Homogenized to Fine-Scale Maps for Multiscale PDE. Multiscale Model. Simul. Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators. CoRR Amirhossein Mollaali, Gabriel Zufferey, Gonzalo Constante-Flores, Christian Moya, Can Li, Guang Lin, Meng Yue
2024	J	`jnl`	Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks. CoRR Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin
2024	J	`jnl`	DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients. CoRR Amirhossein Mollaali, Izzet Sahin, Iqrar Raza, Christian Moya, Guillermo Paniagua, Guang Lin
2023	J	`jnl`	B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD. J. Comput. Phys. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions. CoRR Zhihao Kong, Amirhossein Mollaali, Christian Moya, Na Lu, Guang Lin
2023	J	`jnl`	Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	Bayesian, Multifidelity Operator Learning for Complex Engineering Systems-A Position Paper. J. Comput. Inf. Sci. Eng. Christian Moya, Guang Lin
2023	J	`jnl`	D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	DAE-PINN: a physics-informed neural network model for simulating differential algebraic equations with application to power networks. Neural Comput. Appl. Christian Moya, Guang Lin
2023	J	`jnl`	Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles. CoRR Izzet Sahin, Christian Moya, Amirhossein Mollaali, Guang Lin, Guillermo Paniagua
2023	J	`jnl`	DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems. IEEE Syst. J. Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
2023	J	`jnl`	DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid's post-fault trajectories. Neurocomputing Christian Moya, Shiqi Zhang, Guang Lin, Meng Yue
2023	J	`jnl`	Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks. Eng. Appl. Artif. Intell. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training. Algorithms Binghang Lu, Christian Moya, Guang Lin
2023	J	`jnl`	On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators. CoRR Christian Moya, Guang Lin, Tianqiao Zhao, Meng Yue
2022	J	`jnl`	DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems. CoRR Yixuan Sun, Christian Moya, Guang Lin, Meng Yue
2022	J	`jnl`	DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories. CoRR Christian Moya, Shiqi Zhang, Meng Yue, Guang Lin
2022	J	`jnl`	Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks. Algorithms Christian Moya, Guang Lin
2022	J	`jnl`	On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2021	J	`jnl`	Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2021	J	`jnl`	DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks. CoRR Christian Moya, Guang Lin
2020	J	`jnl`	Semantic analysis framework for protecting the power grid against monitoring-control attacks. IET Cyper-Phys. Syst.: Theory & Appl. Jiankang Wang, Gonzalo E. Constante, Christian Moya, Junho Hong
2019	J	`jnl`	Developing correlation indices to identify coordinated cyber-attacks on power grids. IET Cyper-Phys. Syst.: Theory & Appl. Christian Moya, Jiankang Wang
2019	—	`conf`	Semantic-Based Detection Architectures Against Monitoring-Control Attacks in Power Grids. SmartGridComm Gonzalo E. Constante, Christian Moya, Jiankang Wang
2018	J	`jnl`	Application of Correlation Indices on Intrusion Detection Systems: Protecting the Power Grid Against Coordinated Attacks. CoRR Christian Moya, Junho Hong, Jiankang Wang
2017	—	`conf`	Cyber-Attacks to Voltage Control Applications via Wide Area Monitoring, Protection and Control System. SPSR-SG@CPSWeek Christian Moya, Jiankang Wang
2017	J	`jnl`	Developing a Correlation Index to Identify Coordinated Cyber-Attacks to Power Grids. CoRR Christian Moya, Jiankang Wang
2014	C	`conf`	A hierarchical framework for demand-side frequency control. ACC Christian Moya, Wei Zhang, Jianming Lian, Karanjit Kalsi