-
Notifications
You must be signed in to change notification settings - Fork 11
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
a87d98b
commit f9074f1
Showing
1 changed file
with
4 additions
and
4 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,10 +1,10 @@ | ||
| The easiest way to start using pyroVED is via [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb), which is a free research tool from Google for machine learning education and research built on top of Jupyter Notebook. The following notebooks can be executed in Google Colab by simply clicking on "Open in Colab" icon: | ||
| <br><br> | ||
|
|
||
| * Shift-VAE: Application to 1D spectra with arbitrary offset in peak position [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/master/examples/shiftVAE.ipynb) | ||
| * Shift-VAE: Application to 1D spectra with arbitrary offset in peak position [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/master/examples/shiftVAE.ipynb) | ||
|
|
||
| * r-VAE: Application to arbitrary rotated 2D images [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/master/examples/rVAE.ipynb) | ||
| * r-VAE: Application to arbitrary rotated 2D images [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/master/examples/rVAE.ipynb) | ||
|
|
||
| * j(r)-VAE: Learning (jointly) discrete and continuous representations of the arbitrary rotated image data [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/main/examples/jrVAE.ipynb) | ||
| * j(r)-VAE: Learning (jointly) discrete and continuous representations of the arbitrary rotated image data [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/main/examples/jrVAE.ipynb) | ||
|
|
||
| * ss(r)-VAE: Semi-supervised learning for data with orientational disorder [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/main/examples/ssrVAE.ipynb) | ||
| * ss(r)-VAE: Semi-supervised learning for data with orientational disorder [](https://colab.research.google.com/github/ziatdinovmax/pyroVED/blob/main/examples/ssrVAE.ipynb) |