This module provides ops to perform various mathematical tasks commonly needed when building quantitative finance models. We do not aim to provide exhaustive coverage here. Tensorflow and Tensorflow Probability provide a significant suite of methods already and the methods here are meant to build on those.
Some of the modules/functions provided are:
- math.interpolation: Ops to perform linear and cubic interpolation.
- math.optimizer: Ops for numerical optimization.
- math.pde: Ops to numerically solve partial differential equations using finite difference methods. Currently, only linear second order PDEs are supported as this is the most commonly needed case.
- math.random: Ops to compute low discrepancy sequences.
- math.root_search: Provides the Brent method for computing roots of functions in one dimension.
- math.segment_ops: Utility methods to apply some element wise ops in a segment.