Part V: Advanced Architectures
Specialized neural network designs
Overview
Part V explores specialized architectures that solve particular problems or introduce novel mechanisms. These papers show the creativity and diversity of neural network design beyond standard CNNs, RNNs, and Transformers.
Chapters
| # | Chapter | Key Concept |
|---|---|---|
| 18 | Pointer Networks | Pointing to input positions |
| 19 | Order Matters: Seq2Seq for Sets | Handling unordered inputs |
| 20 | Neural Turing Machines | External differentiable memory |
| 21 | Neural Message Passing | Graph neural networks |
| 22 | Relational Reasoning | Object-relation processing |
| 23 | Variational Lossy Autoencoder | VAE with rate-distortion |
The Diversity
Pointer Networks → Variable-length outputs
Seq2Seq for Sets → Order-invariant processing
Neural Turing Machines → External memory
Message Passing → Graph structures
Relational Reasoning → Pairwise comparisons
VLAE → Compression framework
Key Takeaway
Different problems require different architectures. These papers show how to design networks for specific challenges: combinatorial optimization, graph data, relational reasoning, and more.
Prerequisites
- Parts I-IV (helpful for understanding design principles)
- Familiarity with basic architectures
- Interest in specialized applications
What You’ll Be Able To Do After Part V
- Design networks for specific problem types
- Understand graph neural networks
- Apply memory-augmented architectures
- See connections between different specialized designs