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Home Page: https://coggle.it/diagram/Wf5mYoJbsgABUF9P
Deep Learning Architecture Genealogy Project
Home Page: https://coggle.it/diagram/Wf5mYoJbsgABUF9P
RL is a method of training. The actual NN used are often pretty standard feed-forward NN.
One counter-example could be value iteration networks: https://arxiv.org/abs/1602.02867
But I would classify these separately.
Neural Turing Machine (2014.10) https://arxiv.org/pdf/1410.5401.pdf
Hybrid Computing using a neural network with dynamic external memory (2016.10) https://www.nature.com/nature/journal/v538/n7626/full/nature20101.html
Neural Programmer (2016.08) https://arxiv.org/pdf/1511.04834.pdf
Neural Random-Access Machines (2016.02) https://arxiv.org/pdf/1511.06392.pdf
Neural GPUs Learn Algorithms (2016.03) https://arxiv.org/pdf/1511.08228.pdf
Learning Efficient Algorithm with Hierarchical Attentive Memory (2016.02) https://arxiv.org/abs/1602.03218
The paper link of infoGAN is linked to Improved Training of Wasserstein GANs.
Under CNN category, should it be GoogleNet instead of GoggleNet?
It's better to have a separate data file (preferrably, yaml format)
and let the python script autogenerates the markdown file.
I guess there is a data file(Neural Net Arch Genealogy.txt
),
but it's not included in the repository because of the gitignore.
with open('Neural Net Arch Genealogy.txt') as fin, open('README.md', 'w') as fout:
fout.write(head)
for line in fin:
tab_count = line.count('\t')
if not tab_count:
continue
spaces = [' ' for i in range(tab_count-1)]
fout.write(''.join(spaces) + '* ' + line.replace('\t', ''))
fout.write(tail)
For example,
name
, date
, link
data
It would look like this
---
Memory Networks:
data:
- name: Memory Network
date: '14.10'
link: https://arxiv.org/abs/1410.3916
- name: End to End Memory Network
date: '15.03'
link: https://arxiv.org/pdf/1503.08895.pdf
Neural Programming:
data:
- name: Neural Turing Machine
date: '14.10'
link: https://arxiv.org/pdf/1410.5401.pdf
- name: Neural Random-Access Machine
date: '16.02'
link: https://arxiv.org/pdf/1511.06392.pdf
CNN:
data:
- name: Some CNNs
date: Some Cnn Date
link: Some CNN Link
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