Stochastic_Depth
Deep Networks with Stochastic Depth (by yueatsprograms)
dropout
Code release for "Dropout Reduces Underfitting" (by facebookresearch)
| Stochastic_Depth | dropout | |
|---|---|---|
| 3 | 1 | |
| 467 | 308 | |
| - | 0.0% | |
| 10.0 | 3.2 | |
| over 5 years ago | 12 months ago | |
| Lua | Python | |
| - | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stochastic_Depth
Posts with mentions or reviews of Stochastic_Depth.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-05.
-
[R] [N] Dropout Reduces Underfitting - Liu et al.
It's actually, for every layer in the ResNet, dropping everything else except residual connections with a probability p. See this paper Deep Network with Stochastic Depth
-
[Discussion] Stochastic Depth with BatchNorm ?
Found relevant code at https://github.com/yueatsprograms/Stochastic_Depth + all code implementations here
- [D] Anyone still using Stochastic Depth?
dropout
Posts with mentions or reviews of dropout.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-05.
What are some alternatives?
When comparing Stochastic_Depth and dropout you can also consider the following projects:
vision - Datasets, Transforms and Models specific to Computer Vision