Methods › Sequential › Temporal Convolutions › TaLK Convolution
Time-aware Large Kernel Convolution
TaLK Convolution
Introduced by Vasileios Lioutas et al. in Time-aware Large Kernel Convolutions
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Time-aware Large Kernel (TaLK) convolution is a type of temporal convolution that learns the kernel size of a summation kernel for each time-step instead of learning the kernel weights as in a typical convolution operation. For each time-step, a function is responsible for predicting the appropriate size of neighbor representations to use in the form of left and right offsets relative to the time-step.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Time-aware Large Kernel Convolutions 8 Feb 2020 · 1 repository · arXiv:2002.03184Syntology ran 5 of 7 samples · 2 unverified
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Document Summarization | 1 |
| Language Modeling | 1 |
| Language Modelling | 1 |
| Machine Translation | 1 |
| Translation | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections