STLearner

A beginner for spatial-temporal data and time series.
#spatiotemporal #uncertainty #timeseries

[STLearner @learner_st]

@Elaina43114880 @JustinLin610 @_TobiasLee maybe sun xu老师

[STLearner @learner_st]

@scaling01 kaichao is amazing!

[STLearner @learner_st]

@anas_ant THX!

[STLearner @learner_st]

@anas_ant Just like the next token predication? I guess.

[STLearner @learner_st]

@yiwenyuan98 I just saw this photo in your Rednote(小红书) 😄.

[STLearner @learner_st]

@annadgoldie thank you

[STLearner @learner_st]

@anas_ant @dpfoser I have noticed this work. It's an excellent work!

[STLearner @learner_st]

📰In-Context Fine-Tuning for Time-Series Foundation Models
https://t.co/QnRO3RYqFR
📷Md Atik Ahamed, Qiang ChengConvolutional Network [UT Austin, Google]
🔥Keywords: TSFM, In-context Fine-Tuning
#timeseries #LLM #Google

[STLearner @learner_st]

@adad8m Interesting! I saw the original KAN paper also is in this list.😂

[STLearner @learner_st]

@2prime_PKU Just wait. Mamba is also rejected by ICLR. But Mamba2 is accepted by ICML.

[STLearner @learner_st]

@mai_gch @lao_ni Congrats!

[STLearner @learner_st]

@liuzhuang1234 NeurIPS is worse. I dont't think 4000+ acceptances are all solid and insightful.

[STLearner @learner_st]

@realhuawei Congrats! Prof. Wei!

[SIGKDD 2026 @kdd_news]

Thanks to all the reviewers and area chairs of #KDD2024! Your service contributes in making the quality of KDD papers outstanding!

A special mention to the best reviewers of the Research and ADS tracks! 🏆

[STLearner @learner_st]

@xiayutong618 Fine. He is very busy.

[STLearner @learner_st]

@xf1280 You have the same name. Interesting! Congrats!

[STLearner @learner_st]

@shjuiuc Congrats!

[STLearner @learner_st]

@gan_chuang I think that is CAAI? Not CCF.