| Physics-constrained Bayesian inference of state functions in classical density-functional theory | Oct 7, 2020 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 | 0 |
| Learning particle swarming models from data with Gaussian processes | Jun 4, 2021 | FrictionGaussian Processes | —Unverified | 0 | 0 |
| Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac | Nov 11, 2024 | ManagementUncertainty Quantification | —Unverified | 0 | 0 |
| Data-driven method for real-time prediction and uncertainty quantification of fatigue failure under stochastic loading using artificial neural networks and Gaussian process regression | Mar 11, 2021 | Decision MakingGPR | —Unverified | 0 | 0 |
| Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures | Nov 1, 2023 | Gaussian ProcessesUncertainty Quantification | —Unverified | 0 | 0 |
| Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares | May 23, 2025 | Density Estimationparameter estimation | —Unverified | 0 | 0 |
| Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective | Jan 5, 2024 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Data-driven polynomial chaos expansion for machine learning regression | Aug 9, 2018 | BIG-bench Machine Learningregression | —Unverified | 0 | 0 |
| Data-Driven Prediction and Uncertainty Quantification of PWR Crud-Induced Power Shift Using Convolutional Neural Networks | Jun 27, 2024 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models | Mar 23, 2019 | regressionTime Series Analysis | —Unverified | 0 | 0 |
