The Expressive Power of Neural Networks: A View from the Width
文章目录 概 主要内容 定理1 定理2 定理3 定理4 定理1的证明 Lu Z, Pu H, Wang F, et al. The expressive power of neural networks: a view from the width[C]. neural information processing systems, 2017: 6232-6240. @article{lu2017
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相关文章
- 1. The Unreasonable Effectiveness of Recurrent Neural Networks
- 2. On the Number of Linear Regions of Deep Neural Networks
- 3. Exploring the teaching of deep learning in neural networks
- 4. the english of the simple view
- 5. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 6. [paper]Towards Evaluating the Robustness of Neural Networks(C&W)
- 7. Why LSTMs Stop Your Gradients From Vanishing: A View from the Backwards Pass
- 8. On the difficulty of training Recurrent Neural Networks
- 9. The Rise of Meta Learning
- 10. Applications of Graph Neural Networks