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3rd party extensions and code
Jan Schlüter edited this page Sep 8, 2017
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This page lists various projects that make use of Lasagne or implement additional functionality to be used with the library, such as Layer
subclasses and helper functions.
- nolearn: scikit-learn compatible wrappers for neural net libraries, including Lasagne, and other utilities
- craffel's fork: Colin Raffel's fork of Lasagne contains implementations of recurrent and LSTM layers. Merged into the main library in June 2015.
- kaggle-ndsb: winning solution for the National Data Science Bowl on Kaggle (plankton classification)
- lasagne-draw: an implementation of Gregor et al.'s DRAW
- draw_net.py: functions to draw diagrams of a Lasagne network using pydot/graphviz.
- deep_q_rl: an implementation of DeepMind's atari reinforcement learning "deep Q network"
-
transformer_network: Spatial Transformer Network implementation in the form of a
TransformerLayer
class. Merged into the main library in August 2015. - Parmesan Parmesan is a library adding variational and semi-supervised neural network models to Lasagne.
- BinaryConnect: training Deep Neural Networks with binary weights during propagations
- TensorNet: implementation of Novikov et al.'s "Tensorizing Neural Networks" by the first author
- NTM-Lasagne: an implementation of Neural Turing Machines, along with reproductions of experiments from the paper.
- neural-doodle: implementation of semantic style transfer
- AgentNet: a library for Deep Reinforcement Learning and custom recurrences
- Gelato: a library for Bayesian Neural Networks based on Lasagne and PyMC3
- toppings: A wrapper for automating training of Lasagne networks. Additionally provides a Caffe-like interface trough JSON specifications.
- DIGITS Training: A modified DIGITS version to train Lasagne models.