machine learning - What are the benefits of using ReLU over softplus …
Apr 13, 2015 · It is often mentioned that rectified linear units (ReLU) have superseded softplus units because they are linear and faster to compute. Does softplus it still have the advantage of inducing …
machine learning - Why are the softmax, softplus, and softsign ...
Dec 18, 2020 · Also, in practice, are the softplus and softsign functions ever used as the activation functions in neural networks?
machine learning - What are the benefits of using SoftPlus over ReLU ...
Jul 17, 2021 · All the discussions online seem to be centered around the benefits of ReLU activations over SoftPlus. The general consensus seems to be that the use of SoftPlus is discouraged since the …
Does it make sense to use `logit` or `softplus` loss for binary ...
Sep 21, 2018 · Does it make sense to use `logit` or `softplus` loss for binary classification problem? Ask Question Asked 7 years, 3 months ago Modified 5 years, 8 months ago
Approximating leaky ReLU with a differentiable function
Feb 22, 2018 · The ReLU activation function of a neural net can be approximated by the softplus function, which is differentiable. How would you approximate the leaky ReLU with a differentiable …
machine learning - Loss values for Gaussian NLL are negative due to ...
Feb 24, 2025 · changing the epsilon value using a softplus function for the var instead of the max clipping the log var values log_var = tf.clip_by_value(log_var, -5.0, 5.0) None of these work, and so I …
machine learning - ReLU outperforming Softplus - Cross Validated
Oct 17, 2020 · ReLU in general is known to outperform many smoother activation functions. It’s easy to optimize, because it’s half-linear. The advantage when using it is usually speed, so it can be the case …
r - Iterative optimization of alternative glm family - Cross Validated
Apr 18, 2019 · The "softplus" model you have proposed is called a in generalized linear model theory. Technically, the link function is the inverse of your softplus function. I can think of three major ways …
machine learning - Why pure exponent is not used as activation …
Jun 26, 2021 · The ReLU function is commonly used as an activation function in machine learning, as well, as its modifications (ELU, leaky ReLU). The overall idea of these functions is the same: before x …
Which activation function for output layer? - Cross Validated
Jun 12, 2016 · While the choice of activation functions for the hidden layer is quite clear (mostly sigmoid or tanh), I wonder how to decide on the activation function for the output layer. Common choices are …