Unlock: Neural ODEs and Continuous-Depth Networks

Treating neural network depth as a continuous variable: the ODE formulation of residual networks, the adjoint method for memory-efficient backpropagation, the duality with PINNs, the SDE bridge to diffusion models, and the open research frontier.