DeepEcho
Synthetic Data Generation for mixed-type, multivariate time series. (by sdv-dev)
CTGAN
Conditional GAN for generating synthetic tabular data. (by sdv-dev)
| DeepEcho | CTGAN | |
|---|---|---|
| 1 | 2 | |
| 88 | 1,150 | |
| - | 2.9% | |
| 7.6 | 8.5 | |
| 4 days ago | 8 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DeepEcho
Posts with mentions or reviews of DeepEcho.
We have used some of these posts to build our list of alternatives
and similar projects.
CTGAN
Posts with mentions or reviews of CTGAN.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing DeepEcho and CTGAN you can also consider the following projects:
SDV - Synthetic data generation for tabular data
Copulas - A library to model multivariate data using copulas.
Mimesis - Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.
gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.
FAST-RIR - This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.