Explore >> Select a destination
|
You are here 
|
dustintran.com | ||
| | | | |
polukhin.tech
|
|
| | | | | As the field of Deep Learning continues to grow, the demand for efficient and lightweight neural networks becomes increasingly important. In this blog post, we will explore six lightweight neural network architectures. | |
| | | | |
sander.ai
|
|
| | | | | Slides for my talk at the Deep Learning London meetup | |
| | | | |
coen.needell.org
|
|
| | | | | In my last post on computer vision and memorability, I looked at an already existing model and started experimenting with variations on that architecture. The most successful attempts were those that use Residual Neural Networks. These are a type of deep neural network built to mimic specific visual structures in the brain. ResMem, one of the new models, uses a variation on ResNet in its architecture to leverage that optical identification power towards memorability estimation. M3M, another new model, ex... | |
| | | | |
dennybritz.com
|
|
| | | This the thirdpart of the Recurrent Neural Network Tutorial. | ||
