Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
To ensure data integrity
B
To simplify the training process
C
To maintain input-output relationships
D
To enhance model interpretability
Understanding the Answer
Let's break down why this is correct
Answer
Identity mapping in deep learning lets a layer simply pass its input straight through to its output, often by adding the input to the layer’s output. This keeps the original signal available so the network can still learn a small adjustment instead of having to learn everything from scratch. Because the signal can flow unchanged, gradients can travel back through many layers without vanishing, making very deep models trainable. For example, a residual block takes an input vector, processes it, and then adds the original input back to the processed result, so the block can focus on learning only the difference from the identity. This trick lets us build networks with hundreds of layers that still learn effectively.
Detailed Explanation
Identity mapping keeps the input and output in the same form. Other options are incorrect because Some think identity mapping keeps data unchanged, but it is not about data integrity; People may think identity mapping makes training easier, but it does not simplify the learning process.
Key Concepts
Interpretation of models
Topic
Identity Mapping in Deep Models
Difficulty
easy level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1In the context of deep learning, how can identity mapping enhance business applications while facilitating the scaling of models?
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2
Question 2How does identity mapping in deep models primarily benefit the training of neural networks?
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3
Question 3How does identity mapping in deep neural networks help with optimization during training?
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4
Question 4Identity Mapping in deep learning models is to optimizing training as a navigation system is to _____?
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5
Question 5In the context of deep learning, identity mapping is primarily used to maintain the ________ from shallower models, aiding in the training of deeper networks.
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6
Question 6Why does identity mapping in deep neural networks help improve training performance in very deep models?
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7
Question 7Which of the following statements about identity mapping in deep models are true? Select all that apply.
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