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Where does it say that its automatic differentiation feature is new and novel? It actually calls out Theano in the paper: "Like Theano and Chainer, TensorFlow
by zeroxfe 11y ago
Where does it say that its automatic differentiation feature is new and novel? It actually calls out Theano in the paper:
"Like Theano and Chainer, TensorFlow supports symbolic differentiation, thus making it easier to define and work with gradient based optimization algorithms."
EDIT: Okay, I see that you already saw the reference. I guess I didn't find the tone as bad as you did. :-/
- emcq 11y agoIt's confusing but automatic differentiation, symbolic differentiation, and finite differences are all different approaches. "Automatic differentiation" typically refers to reverse order chain rule. Higher level libraries do really neat stuff with it. For example autograd can differentiate much of your numpy calls, even of composed of many complex functions.