Christian Moya

Purdue University West Lafayette — United States

Physics and Astronomy · Physical Sciences

14h-index446citations58works3.12yr avg
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Research Topics

Model Reduction and Neural Networks(19), Smart Grid Security and Resilience(13), Power System Optimization and Stability(8), Network Security and Intrusion Detection(8), Neural Networks and Applications(7)

Publications57 total

DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning
Journal of Computational Physics·2025
A self-adaptive energy-based learning rate for stochastic gradient descent via Vector Auxiliary Variable method
Engineering Applications of Artificial Intelligence·2025
Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators
Neural Networks·2025
FPINN-deeponet: A physics-informed operator learning framework for multi-term time-fractional mixed diffusion-wave equations
Journal of Computational Physics·2025· 4 cited
Conformalized-Kans: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (Kans) in Scientific Machine Learning
SSRN Electronic Journal·2025· 2 citedOpen Access
Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-Trained and Finetuned Attention-Driven Neural Operators
SSRN Electronic Journal·2025· 1 citedOpen Access
An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with Vector Auxiliary Variable Method
SSRN Electronic Journal·2025Open Access
Fpinn-Deeponet: An Operator Learning Framework for Multi-Term Time-Fractional Mixed Diffusion-Wave Equations
SSRN Electronic Journal·2025Open Access
Deeponet as a Multi-Operator Extrapolation Model Distributed Pretraining with Physics-Informed Fine-Tuning
SSRN Electronic Journal·2025Open Access
Conformalized-DeepONet: A distribution-free framework for uncertainty quantification in deep operator networks
Physica D Nonlinear Phenomena·2024· 15 cited
DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning
arXiv (Cornell University)·2024Open Access
An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
arXiv (Cornell University)·2024Open Access
Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators
arXiv (Cornell University)·2024Open Access
Bayesian Deep Operator Learning for Homogenized to Fine-Scale Maps for Multiscale PDE
Multiscale Modeling and Simulation·2024· 11 cited
D2NO: Efficient handling of heterogeneous input function spaces with distributed deep neural operators
Computer Methods in Applied Mechanics and Engineering·2024· 15 citedOpen Access
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks
arXiv (Cornell University)·2024· 2 citedOpen Access
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
arXiv (Cornell University)·2024· 3 citedOpen Access
A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients
Fluids·2023· 2 citedOpen Access
B-LSTM-MIONet: Bayesian LSTM-based Neural Operators for Learning the Response of Complex Dynamical Systems to Length-Variant Multiple Input Functions
arXiv (Cornell University)·2023Open Access
A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients
arXiv (Cornell University)·2023Open Access
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Frequent Co-authors

Guang Lin(30), Amirhossein Mollaali(9), Zecheng Zhang(7), Jiankang Wang(7), Yue Meng(4), İzzet Şahin(4), Guillermo Paniagua(4), Lu Lu(4), Hayden Schaeffer(4), Gonzalo E. Constante‐Flores(4), Jianming Lian(3), Karanjit Kalsi(3), Zecheng Zhang(3), Guang Lin(3), Wei Zhang(2), Yixuan Sun(2), Laurentiu Marinovici(2), Junho Hong(2), J.K. Wang(2), Benjamin C.‐Y. Lu(2)