Description

Book Synopsis

Chapter 1. Introduction.- Part I Fundamentals.- Chapter 2. Deep Learning.- Chapter 3. Topological Data Analysis.- Part II Interactions.- Chapter 4. Challenges in Deep Learning.- Chapter 5. Input and Output Spaces.- Chapter 6. Internal Representations and Activations.- Chapter 7. Training Dynamics and Loss Functions.- Chapter 8. Challenges, Future Directions, and Conclusions.

Topological Data Analysis for Neural Networks

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    A Paperback by Rubén Ballester

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      Book details

      Publisher Springer
      Published 17 November 2025
      ISBN-13 9783032082824
      978-3032082824

      Description

      Book Synopsis

      Chapter 1. Introduction.- Part I Fundamentals.- Chapter 2. Deep Learning.- Chapter 3. Topological Data Analysis.- Part II Interactions.- Chapter 4. Challenges in Deep Learning.- Chapter 5. Input and Output Spaces.- Chapter 6. Internal Representations and Activations.- Chapter 7. Training Dynamics and Loss Functions.- Chapter 8. Challenges, Future Directions, and Conclusions.

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