How deep is deep enough? -- Quantifying class separability in the hidden layers of deep neural networks

5 November 2018

Papers citing "How deep is deep enough? -- Quantifying class separability in the hidden layers of deep neural networks"

4 / 4 papers shown

Title
SCHEME: Scalable Channel Mixer for Vision Transformers Deepak Sridhar Yunsheng Li Nuno Vasconcelos 81 0 0 01 Dec 2023
Decision support from financial disclosures with deep neural networks and transfer learning Mathias Kraus Stefan Feuerriegel AIFin 67 262 0 11 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 276 8,878 0 25 Aug 2017
Learning Transferable Architectures for Scalable Image Recognition Barret Zoph Vijay Vasudevan Jonathon Shlens Quoc V. Le 172 5,596 0 21 Jul 2017