CTGAN VS DeepEcho

Compare CTGAN vs DeepEcho and see what are their differences.

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CTGAN DeepEcho
2 1
1,273 105
2.4% 3.8%
8.3 7.5
4 days ago 4 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.

CTGAN

Posts with mentions or reviews of CTGAN. We have used some of these posts to build our list of alternatives and similar projects.

DeepEcho

Posts with mentions or reviews of DeepEcho. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing CTGAN and DeepEcho you can also consider the following projects:

SDV - Synthetic data generation for tabular data

trainer - Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs.

Copulas - A library to model multivariate data using copulas.

DoppelGANger - [IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

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.

gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.

Mimesis - Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.

SDGym - Benchmarking synthetic data generation methods.

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