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Found 3 papers, 2 papers with code
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
Understanding generalization in deep learning is arguably one of the most important questions in deep learning.
Towards Task and Architecture-Independent Generalization Gap Predictors
We also show results for architecture-independent, task-independent, and out-of-distribution generalization gap prediction tasks.
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention.
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