TIDE is described in "TIDE: Time Derivative Diffusion for Deep Learning on Graphs", by Maysam Behmanesh*, Maximilian Krahn*, Maks Ovsjanikov Abstract A prominent paradigm for graph neural networks is ...

Derivative Grapher This is a program that graphs a function from user input, and its derivative, as well as the tanget line corresponding to the derivative.

The new algorithm, D*, computes efficient symbolic derivatives for these functions by symbolically executing the expression graph at compile time to eliminate common subexpressions and by exploiting ...

Constructing the Graph of the Derivative of f (x)=sin (x) Move the point T along the graph of y=sin (x) by moving the slider. The slope function (derivative) is then traced out in blue. Can you ...

The D* algorithm computes efficient symbolic derivatives for these functions by symbolically executing the expression graph at compile time to eliminate common subexpressions and by exploiting the ...

In this letter, we propose a bio-inspired derivative-free optimization algorithm capable of minimizing objective functions with vanishing or exploding gradients. The proposed method searches for ...