Feedforward Networks
Feedforward Network
A Feedforward Network, or a Multilayer Perceptron (MLP), is a neural network with solely densely connected layers. This is the classic neural network architecture of the literature. It consists of inputs $x$ passed through units $h$ (of which there can be many layers) to predict a target $y$. Activation functions are generally chosen to be non-linear to allow for flexible functional approximation.
Image Source: Deep Learning, Goodfellow et al
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Generation | 48 | 9.70% |
| Semantic Segmentation | 45 | 9.09% |
| Self-Supervised Learning | 27 | 5.45% |
| General Classification | 26 | 5.25% |
| Image Classification | 25 | 5.05% |
| Object Detection | 25 | 5.05% |
| Conditional Image Generation | 15 | 3.03% |
| Instance Segmentation | 12 | 2.42% |
| Self-Supervised Image Classification | 8 | 1.62% |
Dense Connections