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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)
| Date | Stars |
|---|---|
| 2026-07-24 | 602 |
| 2026-07-25 | 602 |
| 2026-07-28 | 602 |
| 2026-07-30 | 602 |
| 2026-08-06 | 602 |
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growth rate 0.00%/day
# Transformer_Time_Series DISLCLAIMER: THIS IS NOT THE PAPERS CODE. THIS DOES NOT HAVE SPARSITY. THIS IS TEACHER FORCED LEARNING. Only tried to replicate the simple example without sparsity. [Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting](https://arxiv.org/pdf/1907.00235.pdf) (NeurIPS 2019) Able to match the results of the paper for the synthetic dataset as shown in the table below  The synthetic dataset was constructed as shown below  A nice visualization of how the attention layers look at the signal for predicting the last timestep t=t0+24-1    
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3843b283093b5133, topic:transformer