Empirical Evaluation of Rectified Activations in Convolution Network
machine learning - What are the advantages of ReLU over sigmoid function in deep neural networks? - Cross Validated
Activation Functions : Sigmoid, tanh, ReLU, Leaky ReLU, PReLU, ELU, Threshold ReLU and Softmax basics for Neural Networks and Deep Learning | by Himanshu S | Medium
What are some good Activation Functions other than ReLu or Leaky ReLu? - Quora
Different Activation Functions for Deep Neural Networks You Should Know | by Renu Khandelwal | Geek Culture | Medium
FReLU: Flexible Rectified Linear Units for Improving Convolutional Neural Networks
Empirical Evaluation of Rectified Activations in Convolutional Network – arXiv Vanity
Activation Functions Explained - GELU, SELU, ELU, ReLU and more
What makes ReLU so much better than Linear Activation? As half of them are exactly the same. - Quora
Rectifier (neural networks) - Wikipedia
SELU vs RELU activation in simple NLP models | Hardik Patel
Attention mechanism + relu activation function: adaptive parameterized relu activation function | Develop Paper
Why Relu? Tips for using Relu. Comparison between Relu, Leaky Relu, and Relu-6. | by Chinesh Doshi | Medium
What makes ReLU so much better than Linear Activation? As half of them are exactly the same. - Quora
8: Illustration of output of ELU vs ReLU vs Leaky ReLU function with... | Download Scientific Diagram
Gaussian Error Linear Unit Activates Neural Networks Beyond ReLU | Synced
What makes ReLU so much better than Linear Activation? As half of them are exactly the same. - Quora
Swish Vs Mish: Latest Activation Functions – Krutika Bapat – Engineering at IIIT-Naya Raipur | 2016-2020
Swish: Booting ReLU from the Activation Function Throne | by Andre Ye | Towards Data Science
Meet Mish: New Activation function, possible successor to ReLU? - fastai users - Deep Learning Course Forums
Swish Vs Mish: Latest Activation Functions – Krutika Bapat – Engineering at IIIT-Naya Raipur | 2016-2020
Leaky Relu vs Rectification – everything about my thoughts
