Posts Tagged ‘tutorial’

Glucose Manuscripts

September 14, 2025

some tutorials on flow-matching:
https://arxiv.org/pdf/2412.06264
https://arxiv.org/pdf/2506.02070

Lipman, Y., Havasi, M., Holderrieth, P., Shaul, N., Le, M., Karrer, B., Chen, R. T. Q., Lopez-Paz, D., Ben-Hamu, H., & Gat, I. (2024, December 9). Flow matching guide and code. arXiv.org.
https://arxiv.org/abs/2412.06264

(Sometimes difficult to follow formalism)

Holderrieth, P., & Erives, E. (2025). MIT Class 6.S184: Generative AI with Stochastic Differential equations (pp. 1–52).
https://arxiv.org/pdf/2506.02070
OR
Holderrieth, P., & Erives, E. (2025, June 2). An introduction to flow matching and diffusion models. arXiv.org.
https://arxiv.org/abs/2506.02070

(Very intuitive!!!)

A computational pipeline for spatial mechano-transcriptomics | Nature Methods

September 7, 2025

https://www.nature.com/articles/s41592-025-02618-1

Hallou, A., He, R., Simons, B. D., & Dumitrascu, B. (2025). A computational pipeline for spatial mechano-transcriptomics. Nature Methods. https://doi.org/10.1038/s41592-025-02618-1

Reviews:
https://www.nature.com/articles/s41580-023-00583-1#Sec35
(difficult to follow)

Combining with Spatial transcriptomics:
https://www.nature.com/articles/s41592-025-02618-1
(new thing)

The Algorithmic Foundations of Differential Privacy

July 14, 2025

https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf

The Algorithmic Foundations of Differential Privacy
Cynthia Dwork
Microsoft Research, USA
Aaron Roth
University of Pennsylvania, USA

Foundations and Trends in Theoretical Computer Science, NOW Publishers. 2014.

a few documents from our meeting

July 12, 2025

Gilbert, J. A., & Hartmann, E. M. (2024). The indoors microbiome and human health. Nature Reviews Microbiology, 22(12), 742–755.
https://doi.org/10.1038/s41579-024-01077-3

An updated 2024 indoor microbiome and human health review from Nature Reviews Microbiology.

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development – PMC

June 10, 2025

https://pmc.ncbi.nlm.nih.gov/articles/PMC11513550/

Ponce‐Bobadilla, A. V., Schmitt, V., Maier, C. S., Mensing, S., & Stodtmann, S. (2024). Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development. Clinical and Translational Science, 17(11).
https://doi.org/10.1111/cts.70056

Suffix Array and BWT Explaination

May 18, 2025

The book with a nice explanation of suffix array and BWT is
Bioinformatics Algorithms: An Active Learning Approach by Phillip Compeau & Pavel Pevzner. https://www.bioinformaticsalgorithms.org/

Huntington disease: new insights into molecular pathogenesis and therapeutic opportunities | Nature Reviews Neurology

May 17, 2025

https://www.nature.com/articles/s41582-020-0389-4

Tabrizi, S. J., Flower, M. D., Ross, C. A., & Wild, E. J. (2020). Huntington disease: new insights into molecular pathogenesis and therapeutic opportunities. Nature Reviews Neurology, 16(10), 529–546. https://doi.org/10.1038/s41582-020-0389-4

lecture note on mixed state and density matrix

May 11, 2025

https://www.henryyuen.net/classes/spring2022/
https://www.henryyuen.net/spring2022/lec2-mixed-states.pdf

lecture notes on mixed states and density matrix.

QT:{{”
Frontiers of Quantum Complexity and Cryptography Lecture 2 – Mixed States and Density Matrices
Lecturer: Henry Yuen Spring 2022
Scribes: Melody Hsu

In the third lecture, we wrapped up a review of the foundational concepts we will need to tackle
later topics, and then started our first quantum complexity topic, state tomography. We briefly
discussed several ways to analyze probabilistic mixtures of quantum states; after the conclusion of
the review, we explored lower bounds on complexity of a classic tomography protocol.
“}}

gen ai book

April 20, 2025

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

1906.02691 An Introduction to Variational Autoencoders

March 2, 2025

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