docs: update the documentation;

README.md

@@ -61,12 +61,16 @@ with the missing parts in their data. PyPOTS will keep integrating classical and
 algorithms for partially-observed multivariate time series. For sure, besides various algorithms, PyPOTS is going to
 have unified APIs together with detailed documentation and interactive examples across algorithms as tutorials.
 
+👍 **Please** star this repo to help others notice PyPOTS if you think it is a useful toolkit.
+**Please** properly [cite PyPOTS](https://github.com/WenjieDu/PyPOTS#-citing-pypots) in your publications 
+if it helps with your research. This really means a lot to our open-source research. Thank you!
+
 <a href="https://github.com/WenjieDu/TSDB">
     <img src="https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true" align="left" width="160" alt="TSDB logo"/>
 </a>
 
 To make various open-source time-series datasets readily available to our users,
-PyPOTS gets supported by project [TSDB (Time-Series Data Base)](https://github.com/WenjieDu/TSDB),
+PyPOTS gets supported by its subproject [TSDB (Time-Series Data Base)](https://github.com/WenjieDu/TSDB),
 a toolbox making loading time-series datasets super easy!
 
 Visit [TSDB](https://github.com/WenjieDu/TSDB) right now to know more about this handy tool 🛠!
@@ -173,6 +177,10 @@ PyPOTS supports imputation, classification, clustering, and forecasting tasks on
 
 
 ## ❖ Citing PyPOTS
+**[Updates in Jun 2023]** 🎉A short version of the PyPOTS paper is accepted by the 9th SIGKDD international workshop on 
+Mining and Learning from Time Series ([MiLeTS'23](https://kdd-milets.github.io/milets2023/))). 
+Besides, PyPOTS has been included as a [PyTorch Ecosystem](https://pytorch.org/ecosystem/) project.
+
 The paper introducing PyPOTS is available on arXiv at [this URL](https://arxiv.org/abs/2305.18811),
 and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for
 [Machine Learning Open Source Software](https://www.jmlr.org/mloss/)). If you use PyPOTS in your work,
@@ -240,11 +248,6 @@ We care about the feedback from our users, so we're building PyPOTS community on
 - [WeChat (微信公众号)](https://mp.weixin.qq.com/s/sNgZmgAyxDn2sZxXoWJYMA). We also run a group chat on WeChat,
   and you can get the QR code from the official account after following it;
 
-PyPOTS is also launched on [Product Hunt](https://www.producthunt.com/products/pypots), and we'd love to see your reviews and comments there!
-<a href="https://www.producthunt.com/posts/pypots?utm_source=badge-featured&utm_medium=badge&utm_souce=badge-pypots" target="_blank">
-   <img align='center' src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=399667&theme=light" alt="PyPOTS - a&#0032;Python&#0032;lib&#0032;for&#0032;data&#0032;mining&#0032;on&#0032;PartiallyObserved&#0032;TimeSeries | Product Hunt" style="width: 200px; height: 44px;" width="200" height="44" />
-</a>
-
 If you have any suggestions or want to contribute ideas or share time-series related papers, join us and tell.
 PyPOTS community is open, transparent, and surely friendly. Let's work together to build and improve PyPOTS!
 

docs/index.rst

@@ -76,13 +76,17 @@ Welcome to PyPOTS docs!
 
 ⦿ `Mission`: PyPOTS is born to become a handy toolbox that is going to make data mining on POTS easy rather than tedious, to help engineers and researchers focus more on the core problems in their hands rather than on how to deal with the missing parts in their data. PyPOTS will keep integrating classical and the latest state-of-the-art data mining algorithms for partially-observed multivariate time series. For sure, besides various algorithms, PyPOTS is going to have unified APIs together with detailed documentation and interactive examples across algorithms as tutorials.
 
+👍 **Please** star this repo to help others notice PyPOTS if you think it is a useful toolkit.
+**Please** properly `cite PyPOTS <https://docs.pypots.com/en/latest/index.html#id14>`_ in your publications
+if it helps with your research. This really means a lot to our open-source research. Thank you!
+
 .. image:: https://raw.githubusercontent.com/WenjieDu/TSDB/main/docs/_static/figs/TSDB_logo.svg?sanitize=true
    :width: 170
    :alt: TSDB
    :align: left
    :target: https://github.com/WenjieDu/TSDB
 
-To make various open-source time-series datasets readily available to our users, PyPOTS gets supported by project `TSDB (Time-Series Data Base) <https://github.com/WenjieDu/TSDB>`_, a toolbox making loading time-series datasets super easy!
+To make various open-source time-series datasets readily available to our users, PyPOTS gets supported by its sub-project `TSDB (Time-Series Data Base) <https://github.com/WenjieDu/TSDB>`_, a toolbox making loading time-series datasets super easy!
 
 Visit `TSDB <https://github.com/WenjieDu/TSDB>`_ right now to know more about this handy tool 🛠! It now supports a total of 119 open-source datasets.
 
@@ -140,6 +144,10 @@ Forecasting                    Probabilistic    BTTF (Bayesian Temporal Tensor F
 
 ❖ Citing PyPOTS
 ^^^^^^^^^^^^^^^^
+**[Updates in Jun 2023]** 🎉A short version of the PyPOTS paper is accepted by the 9th SIGKDD international workshop on
+Mining and Learning from Time Series (`MiLeTS'23 <https://kdd-milets.github.io/milets2023/>`_).
+Besides, PyPOTS has been included as a `PyTorch Ecosystem <https://pytorch.org/ecosystem/>`_ project.
+
 The paper introducing PyPOTS is available on arXiv at `this URL <https://arxiv.org/abs/2305.18811>`_.,
 and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for
 `Machine Learning Open Source Software <https://www.jmlr.org/mloss/>`_). If you use PyPOTS in your work,

docs/install.rst

@@ -57,7 +57,7 @@ Although torch-geometric is an optional dependency, we hope things go smoothly w
 Because v2 may cause ``ModuleNotFoundError: No module named 'pandas.core.indexes.numeric'``,
 see https://stackoverflow.com/questions/75953279/modulenotfounderror-no-module-named-pandas-core-indexes-numeric-using-metaflo.
 
-* **Why we need PyTorch >1.10?**
+* **Why we need PyTorch >=1.10?**
 
 Because of pytorch_sparse, please refer to https://github.com/rusty1s/pytorch_sparse/issues/207#issuecomment-1065549338.
 

docs/milestones.rst

@@ -3,6 +3,9 @@ Citation and Milestones
 
 Citing PyPOTS
 ^^^^^^^^^^^^^
+**[Updates in Jun 2023]** 🎉A short version of the PyPOTS paper is accepted by the 9th SIGKDD International Workshop on
+Mining and Learning from Time Series (`MiLeTS'23 <https://kdd-milets.github.io/milets2023/>`_).
+
 PyPOTS paper is available on arXiv at `this URL <https://arxiv.org/abs/2305.18811>`_.,
 and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for
 `Machine Learning Open Source Software <https://www.jmlr.org/mloss/>`_). If you use PyPOTS in your work,
@@ -35,11 +38,14 @@ There are scientific research projects using PyPOTS and referencing in their pap
 Here is `an incomplete list of them <https://scholar.google.com/scholar?as_ylo=2022&q=%E2%80%9CPyPOTS%E2%80%9D&hl=en>`_.
 
 
-Milestones
-^^^^^^^^^^
-- 2022-03: PyPOTS project was initiated;
-- 2022-04: PyPOTS v0.0.1 was released;
-- 2022-09: PyPOTS achieved its first 100 stars on GitHub;
-- 2023-03: PyPOTS was published on Conda-Forge, and users can install it via Anaconda;
-- 2023-04: PyPOTS website was launched, and PyPOTS achieved its first 10K downloads on PyPI;
-- 2023-05: PyPOTS v0.1 was released, and the preprint paper was published on arXiv;
+Project Milestones
+^^^^^^^^^^^^^^^^^^
+- 2022-03: `PyPOTS project <https://github.com/WenjieDu/PyPOTS>`_ is initiated;
+- 2022-04: PyPOTS v0.0.1 is released;
+- 2022-09: PyPOTS achieves its first 100 stars on GitHub;
+- 2023-03: PyPOTS is `published on Conda-Forge <https://anaconda.org/conda-forge/pypots>`_, and users can install it via Anaconda;
+- 2023-04: `PyPOTS website <https://pypots.com>`_ is launched, and PyPOTS achieves its first 10K downloads on PyPI;
+- 2023-05: PyPOTS v0.1 is released, and `the preprint paper <https://arxiv.org/abs/2305.18811>`_ is published on arXiv;
+- 2023-06: A short version of PyPOTS paper is accepted by the 9th SIGKDD International
+  Workshop on Mining and Learning from Time Series (`MiLeTS'23 <https://kdd-milets.github.io/milets2023/>`_);
+- 2023-07: PyPOTS has been accepted as a `PyTorch Ecosystem <https://pytorch.org/ecosystem/>`_ project;