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docs/src/index.md

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 CurrentModule = RecurrentLayers
 ```
 
+<p align="center">
+    <img width="400px" src="assets/logo.png"/>
+</p>
+
 # RecurrentLayers
 
 RecurrentLayers.jl extends [Flux.jl](https://github.com/FluxML/Flux.jl) recurrent layers offering by providing implementations of bleeding edge recurrent layers not commonly available in base deep learning libraries. It is designed for a seamless integration with the larger Flux ecosystem, enabling researchers and practitioners to leverage the latest developments in recurrent neural networks.
+
+## Implemented layers
+
+ - Minimal gated unit as  `MGUCell` [arxiv](https://arxiv.org/abs/1603.09420)
+ - Light gated recurrent unit as `LiGRUCell` [arxiv](https://arxiv.org/abs/1803.10225)
+ - Independently recurrent neural networks as `IndRNNCell` [arxiv](https://arxiv.org/abs/1803.04831)
+ - Recurrent addictive networks as `RANCell` [arxiv](https://arxiv.org/abs/1705.07393)
+ - Recurrent highway network as `RHNCell [arixv](https://arxiv.org/pdf/1607.03474)
+ - Light recurrent unit as `LightRUCell` [pub](https://www.mdpi.com/2079-9292/13/16/3204)
+ - Neural architecture search unit `NASCell` [arxiv](https://arxiv.org/abs/1611.01578)
+ - Evolving recurrent neural networks as `MUT1Cell`, `MUT2Cell`, `MUT3Cell` [pub](https://proceedings.mlr.press/v37/jozefowicz15.pdf)
+ - Structurally constrained recurrent neural network as `SCRNCell` [arxiv](https://arxiv.org/pdf/1412.7753)
+
+## Contributing
+
+Contributions are always welcome! We look for specifically:
+ - Recurrent cells you would like to see implemented 
+ - Benchmarks
+ - Any bugs and mistakes of course!
+ - Documentation, in any form: examples, how tos, docstrings