SDGym
FAST-RIR
| SDGym | FAST-RIR | |
|---|---|---|
| 1 | 1 | |
| 242 | 137 | |
| 1.2% | - | |
| 7.8 | 5.0 | |
| 1 day ago | 6 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
SDGym
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[D] Synthetic data generation techniques for data privacy
I would suggest starting with "differentially private synthetic data generation". These methods utilize differential privacy and mostly protect against membership inference attacks, are very popular in the ML/DL community. I would also suggest reading up on privacy preserving ML methods in general and adversarial attacks against them (membership inference, inversion, reconstruction, property inference), but if you're keen on reading some code, check out sd-gym: https://github.com/sdv-dev/SDGym. The authors have collected implementations for a lot of PPSDG methods. Also I strongly suggest reading McMahan's 2016 paper: https://arxiv.org/abs/1607.00133.
FAST-RIR
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[ICASSP 2022] FAST-RIR: FAST NEURAL DIFFUSE ROOM IMPULSE RESPONSE GENERATOR
Code: https://github.com/anton-jeran/FAST-RIR
What are some alternatives?
Mimesis - Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.
CTGAN - Conditional GAN for generating synthetic tabular data.
SDV - Synthetic data generation for tabular data
DoppelGANger - [IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Copulas - A library to model multivariate data using copulas.
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
DPL - [NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
pyroomacoustics - Pyroomacoustics is a package for audio signal processing for indoor applications. It was developed as a fast prototyping platform for beamforming algorithms in indoor scenarios.