We read CHISEL paper for single-cell copy number variation calling zaccaria2020characterizing in detail today.
We read variational auto-encoder paper kingma2013auto in detail today, with brief disucssion on its single cell application scVI lopez2018deep.
We read three papers: RPCI liu2021robust, Cell-ID: cortal2021gene, scPred alquicira2019scpred, all about linear projection of single-cell transcriptome to lower dimensional space with singular value decomposition (SVD), the implementation technique for Principal component analysis (PCA).
We also referred more details on PCA and SVD by reading the following book chapters:
- SVD quick reading: chapter 2.7-2.8 (4 pages): https://www.deeplearningbook.org/contents/linear_algebra.html
- SVD Longer reading: chapter 4.5: https://mml-book.github.io/book/mml-book.pdf
- PCA quick reading: chapter 12.1 https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
We read the Chapter 8 OptimiZation, PML book 1. https://probml.github.io/pml-book/book1.html
Rongting lead the reading of the foundation part, Mingze lead the discussion of the specific methods (SGD and the rest), and Chen C introduce the EM details.
We read the Chapter 13-14 deep nueral networks(Introduction), PML book 1. https://probml.github.io/pml-book/book1.html
Xianjie, Qiaochen and Ruiyan lead the reading.
We read the Chapter 14 VAE, PML book 1. https://probml.github.io/pml-book/book1.html
Fangxin and weizhong lead the reading.
../bibs/deep_readings.bib