From 0f1977b6dc18137c257eb91a937752e886d43940 Mon Sep 17 00:00:00 2001 From: Wenjie Du Date: Thu, 21 Sep 2023 22:40:25 +0800 Subject: [PATCH] docs: update READE with new added models; --- README.md | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 7b591634..9c86f08a 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,8 @@ -##

Welcome to PyPOTS

+

Welcome to PyPOTS

+ **

A Python Toolbox for Data Mining on Partially-Observed Time Series

**

@@ -161,6 +162,8 @@ 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];
Self-Attention-based Imputation for Time Series [^1];
Note: proposed in [^2], and re-implemented as an imputation model in [^1]. | 2017 | +| 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 | | Neural Net | M-RNN | Multi-directional Recurrent Neural Network [^9] | 2019 | | Naive | LOCF | Last Observation Carried Forward | - | @@ -253,7 +256,7 @@ We care about the feedback from our users, so we're building PyPOTS community on 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! - +[//]: # (Use APA reference style below) [^1]: Du, W., Cote, D., & Liu, Y. (2023). [SAITS: Self-Attention-based Imputation for Time Series](https://doi.org/10.1016/j.eswa.2023.119619). *Expert systems with applications*. [^2]: Vaswani, A., Shazeer, N.M., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., & Polosukhin, I. (2017). [Attention is All you Need](https://papers.nips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html). *NeurIPS 2017*. [^3]: Cao, W., Wang, D., Li, J., Zhou, H., Li, L., & Li, Y. (2018). [BRITS: Bidirectional Recurrent Imputation for Time Series](https://papers.nips.cc/paper/2018/hash/734e6bfcd358e25ac1db0a4241b95651-Abstract.html). *NeurIPS 2018*. @@ -263,7 +266,8 @@ PyPOTS community is open, transparent, and surely friendly. Let's work together [^7]: Jong, J.D., Emon, M.A., Wu, P., Karki, R., Sood, M., Godard, P., Ahmad, A., Vrooman, H.A., Hofmann-Apitius, M., & Fröhlich, H. (2019). [Deep learning for clustering of multivariate clinical patient trajectories with missing values](https://academic.oup.com/gigascience/article/8/11/giz134/5626377). *GigaScience*. [^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*.

🏠 Visits @@ -271,4 +275,4 @@ PyPOTS community is open, transparent, and surely friendly. Let's work together PyPOTS visits
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