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About An Overview of Explanation Approaches For Deep Neural Networks (Ongoing Work-This Is A Draft)
1) Machine learning models like deep neural networks are increasingly being used but their "black box" nature causes concerns about trust, safety, and understanding how they work. 2) There is a need for approaches to explain the behaviors and decisions of deep learning models. Existing interpretable models are not high performing enough for complex tasks like vision and speech recognition. 3) The article reviews existing explanation approaches for deep neural networks and discusses evaluation of explanations and applications enabled by explanations. It aims to help understand, evaluate, and apply explanation approaches.
Detailed Information
| Author: | ['Anton Kuznetsov'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 17 |
| Language: | English |
| Format: | |
| Price: | FREE |
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