Deep learning architectures
The designs of neural networks, from feedforward networks to transformers and state space models.
- Feedforward networks
- Convolutional networks
- Recurrent networks
- Residual and skip connections
- Attention mechanisms
- Transformers
- Position encodings
- State space and linear recurrent models
- Mixture of experts
- Graph neural networks
- Equivariant and geometric networks
- Memory-augmented networks
- Neural ODEs and implicit models
- Hypernetworks and dynamic networks
- Hybrid architectures
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