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Computer Science > Machine Learning

arXiv:2301.07573 (cs)
[Submitted on 18 Jan 2023]

Title:Synthcity: facilitating innovative use cases of synthetic data in different data modalities

Authors:Zhaozhi Qian, Bogdan-Constantin Cebere, Mihaela van der Schaar
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Abstract:Synthcity is an open-source software package for innovative use cases of synthetic data in ML fairness, privacy and augmentation across diverse tabular data modalities, including static data, regular and irregular time series, data with censoring, multi-source data, composite data, and more. Synthcity provides the practitioners with a single access point to cutting edge research and tools in synthetic data. It also offers the community a playground for rapid experimentation and prototyping, a one-stop-shop for SOTA benchmarks, and an opportunity for extending research impact. The library can be accessed on GitHub (this https URL) and pip (this https URL). We warmly invite the community to join the development effort by providing feedback, reporting bugs, and contributing code.
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)
Cite as: arXiv:2301.07573 [cs.LG]
  (or arXiv:2301.07573v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2301.07573

Submission history

From: Zhaozhi Qian [view email]
[v1] Wed, 18 Jan 2023 14:49:54 UTC (129 KB)
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