Enabling Synthetic Data adoption in regulated domains

13 April 2022

Papers citing "Enabling Synthetic Data adoption in regulated domains"

9 / 9 papers shown

Title
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 107 198 0 17 Feb 2021
Statistical stability indices for LIME: obtaining reliable explanations for Machine Learning models Giorgio Visani Enrico Bagli F. Chesani A. Poluzzi D. Capuzzo FAtt 63 170 0 31 Jan 2020
Reconstruction and Membership Inference Attacks against Generative Models Benjamin Hilprecht Martin Härterich Daniel Bernau AAML MIACV 79 191 0 07 Jun 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 73 245 0 24 May 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 150 1,436 0 01 May 2019
CatBoost: gradient boosting with categorical features support Anna Veronika Dorogush Vasily Ershov Andrey Gulin 149 1,342 0 24 Oct 2018
Measuring the quality of Synthetic data for use in competitions James Jordon Jinsung Yoon M. Schaar 64 32 0 29 Jun 2018
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch GAN SyDa MedIm 123 794 0 08 Jun 2017
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 241 2,365 0 15 May 2008