Comments (4)
In GitLab by @lgs on Oct 29, 2020, 10:49
assigned to @lgs
from deepvats.
In GitLab by @lgs on Oct 29, 2020, 11:09
I have updated the 02_DCAE to train it with a papermill experiment and a wandb sweep. I have included the following code to read the parameters from _experiments_papermill_caler.ipynb
ifnone(config.get('variable'), default_value)
I have launched a training sweep to study the val_loss of autoencoders with all possible combinations of the windows_size (range(24,144,12)) and stride (range(1,12,2)) parameters.
from deepvats.
In GitLab by @lgs on Oct 29, 2020, 12:35
After the first sweep, we got 60 DCAE models available here.
When we take the results with a 'val_loss' lower than 0.3, we get a set of 14 models. In these models, it seems that the size of the window is more important to obtain a good-quality autoencoder than the stride. In the graph, we can see that for the models with a val_loss<=0.30, most of the models used windows below 60. In the case of the stride there is not such a clear pattern, but it seems that low strides (high redundancy in the windowing) improves the quality of the models.
I will re-launch a sweep in which the models are calculated with a windows size range(24,72,12) and a stride in individual steps between 1 and 9. To check in more detail what is happening.
from deepvats.
Sweeps should be redone, closing
from deepvats.
Related Issues (20)
- Make dockerfile-conda the default and only option to build
- Parameterize the use of wandb through environmental variables
- Compatibility with RTX 3090
- Add GPU-PCA and GPU-T-SNE as options for the dimensionality reduction
- Speed up model inference with Nvidia TensorRT
- Add time encodings to MVP encoder
- The previous range size in the dygraph plot is lost every time there is a redraw
- Visualisation of clusters in the time series
- Compute clusters from original latent space
- Find a way to access the app without going to Rstuio first
- Interchange artifact name with artifact type
- Point selector, with sorroundings
- App randomly crashes HOT 1
- Add option to colour the projections plot based on the timestamp
- Optimize Dockerfiles
- Integrate Matrix profile
- Modify get_enc_embs to allow for custom batch sizes, and lazy evaluation
- Integration of POLCANet-Repsol
- Cannot access jupyter notebook HOT 4
- Use in multiple machines
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from deepvats.