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Model

DeepConvContext

code release

IMUOpen codeWeights: not released
Code Cite
UnconfirmedCatalog paper date: Not reportedAdded to atlas: Oct 19, 2026
CitationsView DOI record (opens in a new tab)GitHub starsView on GitHub (opens in a new tab)

Activity counts measure attention, not model quality. Missing counts are unknown. Publication status follows the linked source; a listed venue alone does not confirm peer review.

License
CC BY-NC-SA 4.0
Signals
IMU
At a glance
Type
Task model
Modalities
IMU
Form factor
Not reported
Parameters
Not reported
Architecture
Not reported
Venue
Not reported
Year
Not reported
arXiv
Not reported
DOI
Not reported
Code
Open (opens in a new tab)
Weights
Not released
Licence
CC BY-NC-SA 4.0
Caveats
Not reported
Datasets
Not reported
Papers
Added
Oct 19, 2026
Updated
Oct 19, 2026

Original description

To rerun the experiments without changing anything about the config files, please place the complete dataset download into a folder called data in the main directory of the repository. The folder job_scripts contains collections of commands of all experiments.

Verbatim fromGitHub· Description from the repository README; licence: NOASSERTION

DeepConvContext: ChatPPG research summary card

How it works

How DeepConvContext works: Input signals → Model → Downstream tasksInput signals: IMU (Accelerometer, 3-axis). Model: DeepConvContext.Input signalsIMU: Accelerometer, 3-axisxyzIMUAccelerometer, 3-axisModelDeepConvContext
Inputs
IMU
Approach
code release · no weights

Datasets

No public datasets linked yet.

Papers· 1

Cite

APA

DeepConvContext. (n.d.).

BibTeX

@misc{deepconvcontextdeepconvcontext,
  title         = {{DeepConvContext}}
}

Built from the hub record. Check it against the publisher before submitting.

History

  1. Added to the ChatPPG research hub