Feedback Network

Feedback networks, a class of neural network architectures incorporating recurrent or iterative information flow, aim to improve model performance and biological plausibility. Current research focuses on developing novel algorithms like Feedback-Feedforward Alignment and Layer-wise Feedback Propagation, and applying feedback mechanisms to diverse tasks such as image generation, visual inference, and signal processing, often utilizing architectures like recurrent networks and transformers. These advancements offer potential improvements in efficiency, accuracy, and biological realism for various machine learning applications, particularly in areas like computer vision and communication systems.