Norse

This release features a lot of quality-of-life improvements. Most notably, we started testing for `torch.compile` support, which gives us [significant speedup](https://open-neuromorphic.org/blog/spiking-neural-network-framework-benchmarking/). The improvements gained by moving to `torch.compile` meant that we could safely remove the C++ code such that Norse now is a Python-only module. That means the installations should be significantly faster.

We also added initialization methods for spatial and temporal receptive fields, added support for [NIR](https://github.com/neuromorphs/nir), cleaned up the docs, restructured the imports, removed unnecessary (and slow) try-catch clauses, and cleaned up dependencies.

New state tuples
We also added tentative support for a new [StateTuple implementation](https://github.com/norse/norse/blob/4f729507681e76c5c9f785954026b7d89e7c643b/norse/torch/utils/pytree.py#L67) based on PyTorch's pytrees, which makes it easier to operate on parameters. This allows us to cast parameters to devices or

python
p = LIFParameters(...) Create a parameter
p.to("cuda:0") Cast the parameters to a device
p.float() Cast the parameters to floats.

Note that this is currently only implemented for `LIFParameters` and `LIFBoxParameters`. Let us know how it works!

What's Changed
* Feature li box by Jegp in https://github.com/norse/norse/pull/367
* Feature rf by Jegp in https://github.com/norse/norse/pull/368
* Added pytree state and support for torch.compile by Jegp in https://github.com/norse/norse/pull/349
* Adds NIR export by Jegp in https://github.com/norse/norse/pull/371
* Constrain pytorch-lightning version in example tasks README by 4iar in https://github.com/norse/norse/pull/372
* Feature rf by Jegp in https://github.com/norse/norse/pull/376
* Feature docs by Jegp in https://github.com/norse/norse/pull/380
* Feature nir by Jegp in https://github.com/norse/norse/pull/379
* Fix typos by omahs in https://github.com/norse/norse/pull/385
* Added tests for torch.compile by Jegp in https://github.com/norse/norse/pull/386
* Improves spatial receptive field API by Jegp in https://github.com/norse/norse/pull/387
* Remove broken workflows by Jegp in https://github.com/norse/norse/pull/391

New Contributors
* 4iar made their first contribution in https://github.com/norse/norse/pull/372
* omahs made their first contribution in https://github.com/norse/norse/pull/385

**Full Changelog**: https://github.com/norse/norse/compare/v1.0.0...v1.1.0

This is the first stable release of Norse. We feel like that after close to almost 4 years of development it is time to take this step. The API has stabilised somewhat and while we anticipate some changes in the future, we will try to do them in ways that are easy to accommodate for users. Since the last release we mostly focussed on bugs and worked on performance. We also got some nice additions

- Feature spikes to times decoder (321): A differentiable way of encoding spikes to times.
- Feature no delay (326): We changed the integration order of most models
- Feature AdEx refractory (291): Adaptive Exponential Fire Neuron with refractory state

We also worked on improvements to documentation, our continuous integration and build tooling.

This release includes prototypical sparse and adjoint equations, neuron models, utilities, and various stability fixes.

Specifically, we included
* Izhikevich and IAF neuron models (thanks to adelpierre)
* Discrete adjoint sensitivity *and* sparse equations for LIF dynamics
* Efficient convolutions in time (`LConv2d`)
* Triangular surrogate gradients (thanks to Huizerd)
* Preliminary plotting primitives
* Usage improvements for tensor datatypes (from, for instance, Tonic) and parameter settings for JIT optimized code
* Increased code coverage
* Documentation improvements
* Stability improvements around C++ code, sequential state models, and tasks
* Numerous bug fixes, e.g. around recurrent autapses
* Nix support

RC3 for the sparse and adjoint code. Aims to resolve builds for Windows and Linux

RC2 for the sparse and adjoint code. Aims to resolve builds for Windows and Linux