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Neural networks

Notes

Quantization

LayerNorm

Batch normalization

Neural network training

Neural architecture search

Backpropagation

Transformers

Notes on: Git Re-Basin: Merging Models modulo Permutation Symmetries by Ainsworth, S. K., Hayase, J., & Srinivasa, S. (2022)

Gradient descent for wide two-layer neural networks – I : Global convergence

Hopfield Networks

Notes on: Scaling down Deep Learning by Greydanus, S. (2020)

Adversarial examples

Residual neural networks

The Scaling Hypothesis

Memory in neural networks

NEAT

Implicit neural representations

Double descent

Generative adversarial networks

Cellular neural networks

Variational autoencoders

Neural networks as dynamical systems

Graph neural networks

Distillation

Attention

Notes on: Generalization over different cellular automata rules learned by a deep feed-forward neural network by Aach, M., Goebbert, J. H., & Jitsev, J. (2021)

Attractor networks

CPPN

Neural tangent kernel

Notes on: Evolving Neural Networks through Augmenting Topologies by Stanley, K. O., & Miikkulainen, R. (2002)

Notes on: Molecule Attention Transformer by Maziarka, Ł., Danel, T., Mucha, S., Rataj, K., Tabor, J., & Jastrzębski, S. (2020)

Notes on: Neural Circuit Policies Enabling Auditable Autonomy by Lechner, M., Hasani, R., Amini, A., Henzinger, T. A., Rus, D., & Grosu, R. (2020)

Recurrent neural networks

Convolutional neural networks

Adaptive Computation Time

Mean field theory of neural networks (talk)

Autoencoders

Neural network pruning