Generative Deep Learning: teaching machines to paint, write, compose, and play: Foster, David: 9781492041948: Amazon.com: Books. (n.d.). https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947
World Model page 331
Variational Autoencoders page 59
Has detailed setup for ELBO
https://arxiv.org/abs/1906.02691
Kingma, D. P., & Welling, M. (2019). An introduction to variational autoencoders. Foundations and Trends® in Machine Learning, 12(4), 307–392. https://doi.org/10.1561/2200000056
https://arxiv.org/abs/1803.00567
explains the dual problem well
Peyré, G., & Cuturi, M. (2018, March 1). Computational Optimal transport. arXiv.org. https://arxiv.org/abs/1803.00567
tutorial_on_optimal_transport.pdf
https://arxiv.org/abs/2312.07511
Duval, A., Mathis, S., V., Joshi, C. K., Schmidt, V., Miret, S., Malliaros, F. D., Cohen, T., Liò, P., Bengio, Y., & Bronstein, M. (2023, December 12). A Hitchhiker’s guide to Geometric GNNs for 3D atomic Systems. arXiv.org. https://arxiv.org/abs/2312.07511
Good intuition on spherical harmonics
Some tutorials on diffusion models:
[An Arxiv Tutorial]
https://arxiv.org/pdf/2403.18103
https://arxiv.org/abs/2403.18103
Chan, S. H. (2024, March 26). Tutorial on diffusion models for imaging and vision. arXiv.org. https://arxiv.org/abs/2403.18103
has master equation, forward & back SDE, relationship of SDE to p(x)
[Also, Some Useful Blogs]
https://baincapitalventures.notion.site/Diffusion-Without-Tears-14e1469584c180deb0a9ed9aa6ff7a4c https://yang-song.net/blog/2021/score/
https://lilianweng.github.io/posts/2021-07-11-diffusion-models/
https://www.datacamp.com/tutorial/how-transformers-work
How Transformers Work: A Detailed Exploration of Transformer Architecture
Explore the architecture of Transformers, the models that have revolutionized data handling through self-attention mechanisms.
Jan 9, 2024 · 15 min read
https://arxiv.org/abs/1906.02691
Kingma, D. P., & Welling, M. (2019). An introduction to variational autoencoders. Foundations and Trends® in Machine Learning, 12(4), 307–392. https://doi.org/10.1561/2200000056
linkstream2 microblog 