insdout / Time-Series-Hybrid-Autoencoder

Remaining Useful Life estimation and sensor data generation by VAE and diffusion model on C-MAPSS dataset.

Date Created 2022-12-17 (about a year ago)

Commits 116 (last one 6 months ago)

Stargazers 32 (0 this week)

Watchers 2 (0 this week)

Forks 1

License mit

Ranking

RepositoryStats indexes 589,134 repositories, of these insdout/Time-Series-Hybrid-Autoencoder is ranked #554,621 (6th percentile) for total stargazers, and #481,361 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #109,371/117,584.

insdout/Time-Series-Hybrid-Autoencoder is also tagged with popular topics, for these it's ranked: pytorch (#5,758/5977), time-series (#639/668), diffusion-models (#570/617)

Other Information

insdout/Time-Series-Hybrid-Autoencoder has Github issues enabled, there is 1 open issue and 0 closed issues.

All Topics

vae ddpm c-mapss pytorch time-series latent-space triplet-loss turbofan-engine diffusion-models remaining-useful-life latent-variable-models preventive-maintenance variational-autoencoder classifier-free-guidance conditional-data-generation

Star History

Github stargazers over time

Watcher History

Github watchers over time, collection started in '23

Recent Commit History

116 commits on the default branch (main) since jan '22

Yearly Commits

Commits to the default branch (main) per year

Issue History

Languages

The primary language is Python but there's also others...

Opengraph Image

updated: 2024-11-28 @ 01:31pm, id: 579268011 / R_kgDOIobtqw