docs: update the docs;

WenjieDu · Oct 11, 2023 · 0e89ed3 · 0e89ed3
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diff --git a/README.md b/README.md
@@ -162,6 +162,7 @@ PyPOTS supports imputation, classification, clustering, and forecasting tasks on
 |        **Type**        |  **Abbr.**  |                                                                    **Full name of the algorithm/model/paper**                                                                     | **Year** |
 |       Neural Net       |    SAITS    |                                                               Self-Attention-based Imputation for Time Series [^1]                                                                |   2023   |
 |       Neural Net       | Transformer | Attention is All you Need [^2];<br>Self-Attention-based Imputation for Time Series [^1];<br><sub>Note: proposed in [^2], and re-implemented as an imputation model in [^1].</sub> |   2017   |
+|       Neural Net       |    CSDI     |                                              Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation [^12]                                              |   2021   |
 |       Neural Net       |   US-GAN    |                                                 Generative Semi-supervised Learning for Multivariate Time Series Imputation [^10]                                                 |   2021   |
 |       Neural Net       |   GP-VAE    |                                                              GP-VAE: Deep Probabilistic Time Series Imputation [^11]                                                              |   2020   |
 |       Neural Net       |    BRITS    |                                                              Bidirectional Recurrent Imputation for Time Series [^3]                                                              |   2018   |
@@ -284,7 +285,9 @@ PyPOTS community is open, transparent, and surely friendly. Let's work together
 [^8]: Chen, X., & Sun, L. (2021). [Bayesian Temporal Factorization for Multidimensional Time Series Prediction](https://arxiv.org/abs/1910.06366). *IEEE transactions on pattern analysis and machine intelligence*.
 [^9]: Yoon, J., Zame, W. R., & van der Schaar, M. (2019). [Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks](https://ieeexplore.ieee.org/document/8485748). *IEEE Transactions on Biomedical Engineering*.
 [^10]: Miao, X., Wu, Y., Wang, J., Gao, Y., Mao, X., & Yin, J. (2021). [Generative Semi-supervised Learning for Multivariate Time Series Imputation](https://ojs.aaai.org/index.php/AAAI/article/view/17086). *AAAI 2021*.
-[^11]: Fortuin, V., Baranchuk, D., Raetsch, G. & Mandt, S.. (2020). [GP-VAE: Deep Probabilistic Time Series Imputation](https://proceedings.mlr.press/v108/fortuin20a.html). *AISTATS 2020*.
+[^11]: Fortuin, V., Baranchuk, D., Raetsch, G. & Mandt, S. (2020). [GP-VAE: Deep Probabilistic Time Series Imputation](https://proceedings.mlr.press/v108/fortuin20a.html). *AISTATS 2020*.
+[^12]: Tashiro, Y., Song, J., Song, Y., & Ermon, S. (2021). [CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation](https://proceedings.neurips.cc/paper/2021/hash/cfe8504bda37b575c70ee1a8276f3486-Abstract.html). *NeurIPS 2021*.
+
 
 <details>
 <summary>🏠 Visits</summary>

diff --git a/docs/pypots.imputation.rst b/docs/pypots.imputation.rst
@@ -19,6 +19,15 @@ pypots.imputation.transformer
    :show-inheritance:
    :inherited-members:
 
+pypots.imputation.csdi
+------------------------------
+
+.. automodule:: pypots.imputation.csdi
+   :members:
+   :undoc-members:
+   :show-inheritance:
+   :inherited-members:
+
 pypots.imputation.usgan
 ------------------------------
 

diff --git a/docs/references.bib b/docs/references.bib
@@ -336,20 +336,6 @@ @article{tang2019JointModeling
 keywords = {Computer Science - Machine Learning,Statistics - Machine Learning}
 }
 
-@article{tashiro2021CSDI,
-title = {{{CSDI}}: {{Conditional Score-based Diffusion Models}} for {{Probabilistic Time Series Imputation}}},
-author = {Tashiro, Yusuke and Song, Jiaming and Song, Yang and Ermon, Stefano},
-year = {2021},
-month = oct,
-journal = {arXiv:2107.03502 [cs, stat]},
-eprint = {2107.03502},
-eprinttype = {arxiv},
-primaryclass = {cs, stat},
-url = {http://arxiv.org/abs/2107.03502},
-archiveprefix = {arXiv},
-keywords = {Computer Science - Machine Learning,Statistics - Machine Learning}
-}
-
 @inproceedings{vaswani2017Transformer,
 author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, \L ukasz and Polosukhin, Illia},
 booktitle = {Advances in Neural Information Processing Systems},
@@ -449,4 +435,13 @@ @article{calinski1974
   pages={1--27},
   year={1974},
   publisher={Taylor \& Francis}
-}
+}
+
+@inproceedings{tashiro2021csdi,
+title={{CSDI}: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation},
+author={YUSUKE TASHIRO and Jiaming Song and Yang Song and Stefano Ermon},
+booktitle={Advances in Neural Information Processing Systems},
+editor={A. Beygelzimer and Y. Dauphin and P. Liang and J. Wortman Vaughan},
+year={2021},
+url={https://openreview.net/forum?id=VzuIzbRDrum}
+}