Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
[TMLR 2024] Chronos: Learning the Language of Time Series
Published:
Chronos tokenizes time series values using scaling and quantization into a fixed vocabulary and trains existing transformer-based language model architectures on these tokenized time series via the cross-entropy loss.
[ICLR 2025] Towards Neural Scaling Laws for Time Series Foundation Models
Published:
This paper explores the scaling laws of time series foundations and verifies the prediction performance of two mainstream Transformer architectures, Encoder-only and Decoder-only, on in-distribution and out-of-distribution data on a large-scale time series dataset. 
Predicting multiple observations in complex systems through low-dimensional embeddings
Published:
This article reduces the dimensionality of high-dimensional complex systems through manifold learning and delayed embedding methods, and realizes the modeling and prediction of the complex system in low-dimensional space.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
Published in February 25, 2025
We pre-trained the time series base model on a large-scale synthetic dataset and achieved SOTA performance on five major time series analysis tasks.
Recommended citation: Wang W, Wu K, Li Y B, et al. Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation[J]. arXiv preprint arXiv:2502.15466, 2025.
Download Paper | Download Slides
PySDKit: signal decomposition in Python
Published in February 26, 2025
A Python library for signal decomposition algorithms.
Recommended citation: Wenxuan Wang. (2025). "PySDKit: signal decomposition in Python" Github.
Download Paper | Download Slides
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.