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Found 4 papers, 2 papers with code
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
4D medical images, which represent 3D images with temporal information, are crucial in clinical practice for capturing dynamic changes and monitoring long-term disease progression.
Regularizing Image Classification Neural Networks with Partial Differential Equations
In other words, the knowledge contained by the learned governing equation can be injected into the neural network which approximates the PDE solution function.
Neural Partial Differential Equations
Neural ordinary differential equations (neural ODEs) introduced an approach to approximate a neural network as a system of ODEs after considering its layer as a continuous variable and discretizing its hidden dimension.
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation
We present a method for learning dynamics of complex physical processes described by time-dependent nonlinear partial differential equations (PDEs).
