update doc tutorials

docs/.ipynb_checkpoints/index-checkpoint.rst

@@ -3,31 +3,60 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to Kolmogorov Aarnold Network (KAN) documentation!
+Welcome to Kolmogorov Arnold Network (KAN) documentation!
 ==========================================================
 
-This documentation is for the paper "KAN: Kolmogorov-Arnold Networks" and the github repo can be found here.
-
 .. image:: kan_plot.png
 
-Get the latest news at `CNN`_. (Add links to paper and github repo)
+This documentation is for the `paper`_ "KAN: Kolmogorov-Arnold Networks" and the `github repo`_.
+Kolmogorov-Arnold Networks, inspired by the Kolmogorov-Arnold representation theorem, are promising alternatives
+of Multi-Layer Preceptrons (MLPs). KANs have activation functions on edges, whereas MLPs have activation functions on nodes.
+This simple change makes KAN better than MLPs in terms of both accuracy and interpretability.
+
+.. _github repo: https://github.com/KindXiaoming/pykan
+.. _paper: https://arxiv.org/abs/2404.19756
+
+Installation
+------------
+
+Installation via github
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+   git clone https://github.com/KindXiaoming/pykan.git
+   cd pykan
+   pip install -e .
+   # pip install -r requirements.txt # install requirements
 
-.. _CNN: http://cnn.com/
 
-There are two ways to install kan. The first way is via pip install
+Installation via PyPI
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. code-block:: python
 
-   pip install kan
+   pip install pykan
    
-The second way is via github
+
+Requirements
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. code-block:: python
+   # python==3.9.7
+   matplotlib==3.6.2
+   numpy==1.24.4
+   scikit_learn==1.1.3
+   setuptools==65.5.0
+   sympy==1.11.1
+   torch==2.2.2
+   tqdm==4.66.2
 
-   git clone repolink
-   cd kan
-   pip install -e .
+Get started
+-----------
 
+* Quickstart: :ref:`hello-kan`
+* KANs in Action: :ref:`api-demo`, :ref:`examples`
+* API (advanced): :ref:`api`.
 
 .. toctree::
    :maxdepth: 1
@@ -37,6 +66,9 @@ The second way is via github
    modules.rst
    demos.rst
    examples.rst
+   interp.rst
+   physics.rst
+   community.rst
 
 Indices and tables
 ==================

docs/index.rst

@@ -66,6 +66,9 @@ Get started
    modules.rst
    demos.rst
    examples.rst
+   interp.rst
+   physics.rst
+   community.rst
 
 Indices and tables
 ==================