Josh Izaac

Hi @fran-scala! Before designing an implementation, another option could be to write a demonstration on your paper for https://pennylane.ai/qml/demonstrations/. That is, a Jupyter notebook that showcases the quantum dropout implementation,...

> Do I have to notify you here when I submit the demo? @fran-scala nope! To submit the demo, a pull request simply needs to be made against the https://github.com/pennylaneai/qml...

Thanks @comp-phys-marc! I've let the team know that this PR is review ready.

Hey @cnktysz! We are actually performing dynamic dispatch within the `qml.math` module :) the way it works is: - If a math function is defined in `qml.math`, it defaults to...

Hey @trentfridey! It sounds like missing dependencies; can you see if ``` pip install xanadu-sphinx-theme flaky ``` fixes it?

Hmm, I'm not sure what the most satisfying solution is here. We could: 1. Update the lattice name, but then there is a maintenance overhead 2. Add a disclaimer below...

It might be good to align with the approach taken in the PyQuil documentation

Thanks for documenting this @snicolau! Behind the scenes, the reason for this is that the PennyLane-SF plugin is currently _always_ computing the analytic expectation value, and then using the [Central...

Another comment: this behaviour also leads to a discrepancy between hardware devices (which _do_ currently average samples) and simulators. The above QNode will in fact return discrete samples if executed...

Hi @snicolau! Unfortunately I don't have any updates to report on at the moment -- in order to update the behavior here, this requires a significant refactor of both the...