We are looking into methods to either read or build formulations for neural networks that are sparse, or approximately sparse. For example, connections that are close to zero (given by some user tolerance) can be ignored during model building. Pyomo should already omit weights that are exactly zero when building expressions, but this can speed up model construction.
We are looking into methods to either read or build formulations for neural networks that are sparse, or approximately sparse. For example, connections that are close to zero (given by some user tolerance) can be ignored during model building. Pyomo should already omit weights that are exactly zero when building expressions, but this can speed up model construction.