DiracNets: Training Very Deep Neural Networks Without Skip-Connections - 代码天地

DiracNets: Training Very Deep Neural Networks Without Skip-Connections

其他 2018-11-29 09:41:11 阅读次数: 0

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转载自blog.csdn.net/wydbyxr/article/details/84580154

DiracNets: Training Very Deep Neural Networks Without Skip-Connections

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Training Very Deep Networks论文笔记

Channel Pruning for Accelerating Very Deep Neural Networks

Highway Networks (Training Very Deep Networks, 2015 NIPS)

Mixed-Precision Training of Deep Neural Networks

Channel Pruning for Accelerating Very Deep Neural Networks 论文笔记

[CV Paper] A practical theory for designing very deep convolutional neural networks

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《FRACTALNET: ULTRA-DEEP NEURAL NETWORKS WITHOUT RESIDUALS》阅读笔记

【阅读笔记】Training Deep Neural Networks on Imbalanced Data Sets

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【论文精读】MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels

深层CNN的调参经验 | A practical theory for designing very deep convolutional neural networks

CVPR2017 论文阅读 Channel Pruning for Accelerating Very Deep Neural Networks

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论文笔记：分形网络（FractalNet: Ultra-Deep Neural Networks without Residuals）

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论文翻译：BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or −1

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