[SciPy-user] Automatic Differentiation with PYADOLC and Removing Boost::Python dependency

Sebastian Walter sebastian.walter@gmail....
Fri Mar 27 03:35:04 CDT 2009


On Thu, Mar 26, 2009 at 7:44 PM, Robert Kern <robert.kern@gmail.com> wrote:
> On Thu, Mar 26, 2009 at 12:34, Rob Clewley <rob.clewley@gmail.com> wrote:
>
>> As an example, I would love to use this code in PyDSTool to find
>> derivatives more accurately to compute periodic orbit solutions of
>> differential equations, but it does not appeal to me to require boost
>> as a dependency.
>
> You might want to take a look at Theano as an alternative to automatic
> differentiation:
>
>  http://pylearn.org/theano

I had a quick look at theano. It looks more like symbolic
differentiation. Is that right?
How does it handle functions with loops in the body?

Also, I  have another AD tool on github
(http://github.com/b45ch1/algopy/tree/master) that implements its own
graph structure at the moment.
It might be nice if I could use theano internally to optimize the
computational graph. Do you think that might be possible?


>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma that is made terrible by our own mad attempt to interpret it as
> though it had an underlying truth."
>  -- Umberto Eco
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