Tagged
Neural ODE
PDE and Machine Learning (6): Continuous Normalizing Flows and Neural ODE
How do you turn a Gaussian into a complex data distribution? This article derives Neural ODEs, the adjoint method, continuous normalizing flows (FFJORD), and Flow Matching from the underlying ODE/PDE theory, and shows …
PDE and Machine Learning (5): Symplectic Geometry and Structure-Preserving Networks
Standard neural networks violate conservation laws. This article derives Hamiltonian mechanics, symplectic integrators, HNNs, LNNs, and SympNets from the geometry of phase space.