Vanishing and Exploding Gradients in Deep Networks Questions

Understand the root causes of vanishing and exploding gradients during backpropagation in deep networks. Know mitigation strategies: careful weight initialization (Xavier/He initialization), batch normalization, layer normalization, residual connections, gradient clipping, and architectural choices (skip connections). Discuss how these problems impact training stability and convergence.