debasishg

1. Feature Learning

• Learning Feature Representations with K-means by Adam Coates and Andrew Y. Ng
• The devil is in the details: an evaluation of recent feature encoding methods by Chatfield et. al.
• Emergence of Object-Selective Features in Unsupervised Feature Learning by Coates, Ng
• Scaling Learning Algorithms towards AI Benjio & LeCun
• A Theory of Feature Learning by Brendan van Rooyen, Robert C. Williamson

2. Deep Learning

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever and Ruslan Salakhutdinov
• [Understanding

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

cbergman

- Skelley et al 2013:
  - paper: http://genome.cshlp.org/content/23/9/1496.long
  - ena: http://www.ebi.ac.uk/ena/data/view/SRP018005 (includes RNA-seq)
  - 22 diverse Scer strains
  
- Bergstrom et al 2014
  - paper: https://academic.oup.com/mbe/article-lookup/doi/10.1093/molbev/msu037
  - SGRP2 
  - 19 Scer
  - 22 Spar

cschin