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math-and-ml-notes's Introduction

Links to some important research papers or links. I plan to add notes as I go through each topic one by one.

✔ 1. Information theory based (unsupervised) learning


✔ 2. Disentangled representations

Decided not to delve deeper into this topic. It is not mature yet.
* [Disentangling Disentanglement in Variational Autoencoders](https://arxiv.org/abs/1812.02833)
* [Isolating Sources of Disentanglement in Variational Autoencoders](https://arxiv.org/abs/1802.04942)
* [InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers](https://arxiv.org/abs/1906.06034)
* [Disentangling by Factorising, pdf](https://www.cs.toronto.edu/~amnih/papers/disentangling_nips_ws.pdf)

✔ 3. Self Supervised Learning


✔ 4. Automatic differentiation


5. NNs and ODEs


6. Probabilistic Programming


7. Miscellaneous

Memorization in neural networks

Online Learning

Graph Neural Networks

Normalizing Flows

Transformers

Others


8. Theory of neural networks

Lottery tickets

Others


9. Advanced Variational Inference


10. Causal Inference

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