If the desired signal is not differentiable, then it is not straightforward to solve the tracking problem. In this brief, a methodology based on fractional operators has been suggested to solve this ...

In this paper we present an algorithmic approach for fitting isotonic models under convex, yet non-differentiable, loss functions. It is a generalization of the greedy non-regret approach proposed by ...

By wrapping the function rosenbach2 in jax_finite_difference, it will become completely compatible with JAX's automatic differentiation tooling, and works with other JAX primitives such as vmap.

Q1. Shown below are the graph of two functions . What can one conclude from the above graphs? 1) The product of a differentiable function and a non-differentiable function is ALWAYS differentiable.