You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm just curious, could we combine neural networks with differential equations to represent the unknown parts of equations for training in BrainPy?
For example, like the DiffEqFlux.jl package in Julia.
Thank you!
The text was updated successfully, but these errors were encountered:
Our recent rewrite of the DeepXDE framework: the PINNx framework may meet your demand. PINNx is a library for scientific machine learning and physics-informed learning. It is rewritten according to DeepXDE but is enhanced by our Brain Dynamics Programming (BDP) ecosystem.
Hi,
I'm just curious, could we combine neural networks with differential equations to represent the unknown parts of equations for training in BrainPy?
For example, like the DiffEqFlux.jl package in Julia.
Thank you!
The text was updated successfully, but these errors were encountered: