Nov 28, 2021 · The current paper investigates a simple idea: can test error be predicted using {\em synthetic data,} produced using a Generative Adversarial ...
Jan 28, 2022 · The paper offers a simple method for estimating the performance of deep models without test data using GANs. The empirical results are strong ...
Research on generalization bounds for deep networks seeks to give ways to pre- dict test error using just the training dataset and the network parameters.
Mar 17, 2022 · The current paper investigates a simple idea: can test error be predicted using synthetic data, produced using a Generative Adversarial Network.
The current paper investigates a simple idea: can test error be predicted using synthetic data, produced using a Generative Adversarial Network (GAN) that was ...
Jun 6, 2022 · This blog post describes our ICLR22 spotlight paper, coauthored with Nikunj Saunshi and Arushi Gupta, that gives a surprisingly easy method to ...
Nov 28, 2021 · A recently introduced Predicting Generalization in Deep Learning competition aims to encourage discovery of methods to better predict test error ...
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Aug 29, 2023 · In this tutorial, we will explore how GANs can be used to generate synthetic financial time series data that captures the statistical properties ...
In this competition, the community is invited to propose complexity measures that can accurately predict generalization of models that could potentially ...