donut icon indicating copy to clipboard operation
donut copied to clipboard

WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

Results 26 donut issues
Sort by recently updated
recently updated
newest added

While this paper mainly focus on single dimension time series, are there extensions to deal with multi dimensional time series? For example apply VAE on the feature vector of each...

Hi, how can I set or change the sliding window length? thank you.

Hi, thank you so much for providing this implementation for your paper. Could you please explain in layman's terms what exactly the test_scores mean in regards to the original timeseries...

Hello I am trying to interpret the severity of anomalies using the sample data cpu4.csv and following: > take the negative of the score, if you want something to directly...

hi is there any demo or more detailed tutorial to show us how to run Donut? Thanks, I am a beginner.

Hi Haowen, My data set has continuous points , where each point repesent a day, and not minutes that you have shown in the paper/ sample_data. I had provided a...

When calling the `reconstruct` function in `vae.py` it only returns a single (averaged) value, the reconstruction of the input. Is it possible to access the reconstructions before the averaging is...

Hi, I tried to use Donut for an anomaly detection project. For some reasons, I separate the processes of restoring model and prediction, and problem happened while restoring model. Every...

Dear author, I'm trying to run Donut for the datasets in the sample_data diretory. I found it was quite tricky to get the training porcess converged. Would you please share...