Lasagne: Difference between revisions
From charlesreid1
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* https://github.com/yandexdataschool/Practical_DL - practical deep learning course resources | * https://github.com/yandexdataschool/Practical_DL - practical deep learning course resources | ||
* https://github.com/yandexdataschool/Practical_RL - deep reinforcement learning in the wild | |||
==Implementations of Papers/Example Networks== | ==Implementations of Papers/Example Networks== | ||
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* https://github.com/ferrine/gelato - Bayesian network layers for Lasagne | * https://github.com/ferrine/gelato - Bayesian network layers for Lasagne | ||
* https://github.com/Kadenze/siamese_net - siamese network in Lasagne/Theano | |||
* https://github.com/joelmoniz/gogh-figure - van Gogh style transfer | * https://github.com/joelmoniz/gogh-figure - van Gogh style transfer | ||
Latest revision as of 22:54, 14 October 2017
What is it
Lasagne is a high-level interface for Theano.
Links
Lasagne
Github repo: https://github.com/Lasagne/Lasagne
Documentation: https://lasagne.readthedocs.io/en/latest/
Using Lasagne via Docker: https://lasagne.readthedocs.io/en/latest/user/installation.html#docker
- Can use CPU Docker image, or GPU Docker image (via nvidia-docker)
Github
Lasagne
- https://github.com/Lasagne/Lasagne - main repo
- https://github.com/Kaixhin/dockerfiles - Docker images for Lasagne/Theano
- https://agentnet.readthedocs.io/en/latest/index.html - AgentNet is a toolkit for deep reinforcement learning agent design
Resources/Teaching
- https://github.com/Lasagne/Recipes - Lasagne recipes (examples, models, notebooks, etc.)
- https://github.com/Vict0rSch/deep_learning - Deep learning tutorials and resources for Lasagne+Keras
- https://github.com/lesley2958/deep-learning-python - introduction to deep learning with theano/lasagne
- https://github.com/yandexdataschool/Practical_DL - practical deep learning course resources
- https://github.com/yandexdataschool/Practical_RL - deep reinforcement learning in the wild
Implementations of Papers/Example Networks
- https://github.com/mikesj-public/convolutional_autoencoder - convolutional autoencoder in lasagne/jupyter notebook
- https://github.com/ferrine/gelato - Bayesian network layers for Lasagne
- https://github.com/Kadenze/siamese_net - siamese network in Lasagne/Theano
- https://github.com/joelmoniz/gogh-figure - van Gogh style transfer
- https://github.com/tjwei/GANotebooks - generative adversarial neural network implementations in Lasagne, Keras, and PyTorch
- https://github.com/zalandoresearch/spatial_gan - spatial generative adversarial neural network (one network generates, one network tries to spot the fake stuff)
- https://github.com/luizgh/lasagne_basics - training Lasagne CNN on MNIST data set
- https://github.com/FredericGodin/DynamicCNN - dynamic CNN in Lasagne
- https://github.com/TimSalimans/weight_norm - illustration of weight normalization in Lasagne