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The second bullet point is no longer up-to date: 

antalszava

[BUG] Quanvolution demo results don't match rendered version

14

First noted by a user [here](https://discuss.pennylane.ai/t/not-getting-the-expected-results/986), and confirmed independently by me using a fresh environment with the most recent version of PennyLane and contents of the `qml` repo requirements file....

glassnotes

The stochastic parameter-shift demo is somewhat outdated in terms of the content, and doesn't reflect new understanding of where the stochastic shift rule applies. For example: - it is now...

josh146

The following two pages are due for an upgrade: - https://pennylane.ai/qml/glossary/parameter_shift.html: We should link to our various parameter-shift demos, and update the derivation! It is outdated when compared to latest...

josh146

As part of a demo update (#330), we came across a [demo](https://github.com/PennyLaneAI/qml/blob/master/demonstrations/tutorial_vqe_parallel.py) which requires a little more work in order to update. In this demo, we would like to replace...

Jaybsoni

**Title:** Adaptive circuits for quantum chemistry **Summary:** **Relevant references:** **Possible Drawbacks:** **Related GitHub Issues:**

CatalinaAlbornoz

This is a demo on the updated `RotosolveOptimizer`, complementary to `tutorial_rotoselect` (which also contains Rotsolve for Pauli rotations) and `tutorial_general_parshift` (which details the function reconstruction for more general gates).

dwierichs

Replace usage of `qml.init` with `Template.shape`

10

The `init` module has been deprecated, and the recommend approach for generating initial weights is to use the `Template.shape` method: ```python >>> from pennylane.templates import StronglyEntanglingLayers >>> qml.init.strong_ent_layers_normal(n_layers=3, n_wires=2) #...

josh146

[BUG] TensorFlow version of the backprop tutorial is producing incorrect benchmarks

3

The time scaling plot in the backprop tutorial is currently incorrect:  Strangely enough, the first section of the demo, comparing single forwards and backwards pass times for parameter-shift vs....

josh146

Since PennyLane [PR #959](https://github.com/PennyLaneAI/pennylane/pull/959) optimizers can accept cost functions with non-trainable data, multiple trainable parameters, and keywords. Our demos should reflect this flexibility, instead of using lambda functions and other...

albi3ro