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Investigate #679

1

There are some references to old issues in the repo. In particular #679 seems to show up a lot and have something to do with handling empty Program protos in...

MichaelBroughton

[Discussion] Gradient of state op

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It was pointed out in #256 by @refraction-ray that once we had implemented the adjoint differentiation scheme, it might be possible for us to make our `calculate_state` op differentiable as...

MichaelBroughton

Add adjoint hessian called tfq.math.inner_product_hessian

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This PR adds `tfq.math.inner_product_hessian()` based on adjoint hessian reverse-mode calculation. It's independent of TensorFlow's Jacobian routine, so you can get the Hessian directly without `tf.GradientTape`. **Note**: due to the large...

jaeyoo

This is the first PR to support hessian in TFQuantum. This PR has lots of populating hessian for given parameterized gates.

jaeyoo

Update hello_many_worlds.ipynb

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In this document the `correct` word repeated twice

UsharaniPagadala

Update load_module.py

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Resolves #507

jaeyoo

jaeyoo

Add Quantum Generative Adversarial Networks tutorial

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jaeyoo

TF Quantum Starter Example

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Add a TF Quantum example for beginners to get started with TF Quantum. The notebook demonstrates the following pretty simple operations- - Placing a Qubit - Working with simple quantum...

Rishit-dagli

New tutorial/example for qGAN

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Closes #325 I have written a new tutorial/example jupyter notebook for implementing a qGAN using TFQ and TF-GAN. However, I have been stuck for a while trying to actually get...

oliverob