|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Micrograd||4,842||1||a month ago||1||April 18, 2020||22||mit||Jupyter Notebook|
|A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API|
|Dynamic_neural_manifold||117||4 years ago||other||Jupyter Notebook|
|Gran Dag||74||3 months ago||2||mit||C++|
|Dagnet||72||a year ago||mit||Python|
|PyTorch code for ICPR 2020 paper "DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting"|
|Essence||66||3 years ago||gpl-3.0||Python|
|AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.|
|Nnquery||29||7 years ago||bsd-3-clause||Lua|
|Query complex neural network graph structures in Torch|
What I cannot create, I do not understand - Richard Feynman
A directed acyclic computational graph builder, built from scratch on
C, including auto-differentiation.
This was not just another deep learning library, its minimal code base was supposed to demonstrate how to:
mnist-mlp.py: Depth-2 multi layer perceptron, with ReLU and Dropout; 95.3% on MNIST.
lenet-bn.py: LeNet with Batch Normalization on first layer, 97% on MNIST.
lstm-embed.py: LSTM on word embeddings for Vietnamese Question classification + Dropout + L2 weight decay. 85% on test set and 98% on training set (overfit).
turing-copy.py: A neural turing machine with LSTM controller. Test result on copy task length 70:
visual-answer.py. Visual question answering with pretrained weight from VGG16 and a stack of 3 basic LSTMs, on Glove word2vec.
Q: What is the animal in the picture? . A: cat Q: Is there any person in the picture? . A: no Q: What is the cat doing? . A: sitting Q: Where is the cat sitting on? . A: floor Q: What is the cat color? . A: white Q: Is the cat smiling? . A: yes
dqn-cartpole.py: A classic solved with DQN, with experience replay and target network ofcourse. (Illustration below is one-take)
TODO: Memory network and GAN, for that I need to improve my speed of
conv module first.
GPL 3.0 (see License in this repo)