lixus7 / time-series-works-conferences Goto Github PK
View Code? Open in Web Editor NEWTime-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
License: MIT License
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
License: MIT License
CAMul
is wrong. [CAMul EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting]例如方法ST-SSL中所说的BJTaxi数据集就是TaxiBJ
I want to ask how the stgnn model works
Hi,
Thanks for a great work.
I just made a PR with some minor issues I noticed #9, but there was a larger change I thought of.
Currently, the CCF ranks of the conferences are written for each publication which seems unnecessary. Instead, I think you can just move this information to be under the "Conferences" title. In this way, the information regarding the ranks of the conferences (i.e., what the ranks are, conference average quality, etc.) could also be moved to "Conferences".
Thanks for your great work on collecting time-series papers.
For the paper "FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection", you can find the code at https://github.com/jlidw/FluxEV. Could you please update it? Thanks very much!
Hi,
Thank you for the great work.
This is more of a suggestion than an issue.
Different papers use different weather datasets. So far I have found two: one is from USA weather stations with one-hour aggregation and the other is from Max Plank institute with 10 mins aggregation. Moreover, it looks like different authors are using the Max Plank dataset differently. For example, some of them are using 2 years of data while others are only using one.
I thought about bringing this up in case you want to bring this level of detail. If you want I could help :)
Best.
This is a very cool project!
Hi @lixus7
Thanks for your excellent repo!
Would you mind considering our paper published on ICDE 2023 about diffusion-based imputation models for spatiotemporal time series?
Title: PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
Paper Link: https://arxiv.org/abs/2302.09746
Code Link: https://github.com/LMZZML/PriSTI
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