Update README.md

README.md

@@ -120,7 +120,21 @@ Please refer to ```run_main.py```, ```run_m4.py``` and ```run_pretrain.py``` for
 
 
 ## Further Reading
-1, [**Foundation Models for Time Series Analysis: A Tutorial and Survey**](https://arxiv.org/pdf/2403.14735), in *KDD* 2024.
+1, [**TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis**](https://arxiv.org/abs/2410.16032), in *arXiv* 2024.
+[\[GitHub Repo\]](https://github.com/kwuking/TimeMixer/blob/main/README.md)
+
+**Authors**: Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye, Baichuan Mo, Wenze Lin, Shengtong Ju, Zhixuan Chu, Ming Jin
+
+```bibtex
+@article{wang2024timemixer++,
+  title={TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis},
+  author={Wang, Shiyu and Li, Jiawei and Shi, Xiaoming and Ye, Zhou and Mo, Baichuan and Lin, Wenze and Ju, Shengtong and Chu, Zhixuan and Jin, Ming},
+  journal={arXiv preprint arXiv:2410.16032},
+  year={2024}
+}
+```
+
+2, [**Foundation Models for Time Series Analysis: A Tutorial and Survey**](https://arxiv.org/pdf/2403.14735), in *KDD* 2024.
 
 **Authors**: Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen*
 
@@ -133,7 +147,7 @@ Please refer to ```run_main.py```, ```run_m4.py``` and ```run_pretrain.py``` for
 }
 ```
 
-2, [**Position Paper: What Can Large Language Models Tell Us about Time Series Analysis**](https://arxiv.org/abs/2402.02713), in *ICML* 2024.
+3, [**Position Paper: What Can Large Language Models Tell Us about Time Series Analysis**](https://arxiv.org/abs/2402.02713), in *ICML* 2024.
 
 **Authors**: Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang*, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen*
 
@@ -146,7 +160,7 @@ Please refer to ```run_main.py```, ```run_m4.py``` and ```run_pretrain.py``` for
 }
 ```
 
-3, [**Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook**](https://arxiv.org/abs/2310.10196), in *arXiv* 2023.
+4, [**Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook**](https://arxiv.org/abs/2310.10196), in *arXiv* 2023.
 [\[GitHub Repo\]](https://github.com/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM)
 
 **Authors**: Ming Jin, Qingsong Wen*, Yuxuan Liang, Chaoli Zhang, Siqiao Xue, Xue Wang, James Zhang, Yi Wang, Haifeng Chen, Xiaoli Li (IEEE Fellow), Shirui Pan*, Vincent S. Tseng (IEEE Fellow), Yu Zheng (IEEE Fellow), Lei Chen (IEEE Fellow), Hui Xiong (IEEE Fellow)
@@ -161,7 +175,7 @@ Please refer to ```run_main.py```, ```run_m4.py``` and ```run_pretrain.py``` for
 ```
 
 
-4, [**Transformers in Time Series: A Survey**](https://arxiv.org/abs/2202.07125), in IJCAI 2023.
+5, [**Transformers in Time Series: A Survey**](https://arxiv.org/abs/2202.07125), in IJCAI 2023.
 [\[GitHub Repo\]](https://github.com/qingsongedu/time-series-transformers-review)
 
 **Authors**: Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun
@@ -175,7 +189,7 @@ Please refer to ```run_main.py```, ```run_m4.py``` and ```run_pretrain.py``` for
 }
 ```
 
-5, [**TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting**](https://openreview.net/pdf?id=7oLshfEIC2), in ICLR 2024.
+6, [**TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting**](https://openreview.net/pdf?id=7oLshfEIC2), in ICLR 2024.
 [\[GitHub Repo\]](https://github.com/kwuking/TimeMixer)
 
 **Authors**: Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou