https://github.com/smartgeometry-ucl/dl4g

Example code for the Siggraph Asia Tutorial CreativeAI
https://github.com/smartgeometry-ucl/dl4g

Last synced: about 2 months ago
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Example code for the Siggraph Asia Tutorial CreativeAI

• Host: GitHub
• URL: https://github.com/smartgeometry-ucl/dl4g
• Owner: smartgeometry-ucl
• Created: 2018-04-05T16:01:29.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2019-07-25T16:53:45.000Z (over 5 years ago)
• Last Synced: 2024-08-05T03:02:15.283Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 6.74 MB
• Stars: 547
• Watchers: 39
• Forks: 111
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-google-colab - dl4g - Deep Learning for Graphics (Applications)

README

        
# CreativeAI: Deep Learning for Graphics Tutorial Code

This is the example code accompanying the [CreativeAI: Deep Learning for Graphics](http://geometry.cs.ucl.ac.uk/creativeai/) Course at Siggraph Asia 2018.

These Notebooks can be executed in Google Colaboratory with the following links. Make sure to select a runtime with GPU support (Runtime > Change runtime type) to get the best performance.

## Linear Regression and Polynomial Regression

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/linear_regression.ipynb

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/poly_regression.ipynb

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/poly_regression_polyfit.ipynb

## Stochastic Gradient Descent vs. Gradient Descent

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/sgd.ipynb

## Multi-Layer Perceptron

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/multilayer_perceptron.ipynb

## Edge Filter 'Network'

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/edge_filter.ipynb

## Convolutional Network

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/convolutional_network.ipynb

## Filter Visualizations

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/filter_visualization.ipynb

## Weight Initialization Strategies

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/weight_initialization.ipynb

## Colorization Network

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/colorization.ipynb

## Autoencoder

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/autoencoder.ipynb

## Variational Autoencoder

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/variational_autoencoder.ipynb

## Generative Adversarial Network (GAN)

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/gan.ipynb

## Mirroring with a Convolutional Network

https://colab.research.google.com/github/smartgeometry-ucl/dl4g/blob/master/mirroring.ipynb

## PDE Learning (not available as notebook)

https://github.com/smartgeometry-ucl/dl4g/tree/master/pde_learning