Methods › Sequential › Temporal Convolutions › Causal Convolution

Causal Convolution

27 papers tagged archive 2025-07-28

Introduced by Aaron van den Oord et al. in WaveNet: A Generative Model for Raw Audio

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Causal convolutions are a type of convolution used for temporal data which ensures the model cannot violate the ordering in which we model the data: the prediction p(xₜ₊₁ | x₁, …, xₜ) emitted by the model at timestep t cannot depend on any of the future timesteps xₜ₊₁, xₜ₊₂, …, x_T. For images, the equivalent of a causal convolution is a masked convolution which can be implemented by constructing a mask tensor and doing an element-wise multiplication of this mask with the convolution kernel before applying it. For 1-D data such as audio one can more easily implement this by shifting the output of a normal convolution by a few timesteps.

PaperSource

Papers archive 2025-07-28

27 shown of 27, 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.

Tasks archive 2025-07-28

20 shown of 51 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Time Series6
Time Series Analysis4
Time Series Forecasting4
Speech Recognition3
model3
speech-recognition3
Causal Discovery2
Decoder2
Representation Learning2
Traffic Prediction2
Voice Conversion2
Anomaly Detection1
Audio Generation1
Brain Computer Interface1
Conversational Question Answering1
Denoising1
Density Estimation1
EEG1
ERP1
Edge-computing1

Usage over time archive 2025-07-28

Papers per year tagged with Causal Convolution: 2016 to 2025, peak 6 6 0 2016: 1 paper 2016 2017: 0 papers 2017 2018: 2 papers 2018 2019: 3 papers 2019 2020: 0 papers 2020 2021: 2 papers 2021 2022: 6 papers 2022 2023: 6 papers 2023 2024: 6 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (27 dated). Bars are counts, not a trend claim.

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

Temporal Convolutions

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