565 citations · 723 across the 15 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.CL2021★ 25 cited
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
cs.LG2021★ 1 cited
Reverse Engineering the Neural Tangent Kernel
James B. Simon, Sajant Anand, Michael R. DeWeese
The development of methods to guide the design of neural networks is an important open challenge for deep learning theory. As a paradigm for principled neural architecture design,…