Neural Ordinary Differential Equation
Learning subgrid-scale models with Neural Ordinary Differential Equations
Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems
Stochastic Parameterization and Model Uncertainty in the Lorenz 96 system
Modeling Chaotic Lorenz ODE System using Scientific Machine Learning
Memory-based parameterization with differentiable solver: Application to Lorenz ’96
Learning Reduced Systems via Deep Neural Networks with Memory
Latent ODE for irregularly sampled time series
The road from MLE to EM to VAE
Delay Embedding Forecasting Machine