A curated list of awesome Torch tutorials, projects and communities.
- Applied Deep Learning for Computer Vision with Torch CVPR15 Tutorial [Slides]
- Machine Learning with Torch for IPAM Summer School on Deep Learning. [Code]
- Oxford Computer Science - Machine Learning 2015
- Implementing LSTMs with nngraph
- Community Wiki (Cheatseet) for Torch
- Demos & Turorials for Torch
- Learn Lua in 15 Minutes
Codes and related articles. (#)
means authors of code and paper are different.
- SCRNN (Structurally Constrained Recurrent Neural Network)
- Tomas Mikolov, Armand Joulin, Sumit Chopra, Michael Mathieu, Marc'Aurelio Ranzato, Learning Longer Memory in Recurrent Neural Networks, arXiv:1406.1078 [Paper]
- Tree-LSTM (Tree-structured Long Short-Term Memory networks)
- Kai Sheng Tai, Richard Socher, Christopher D. Manning, Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks, ACL 2015 [Paper]
- LSTM language model with CNN over characters
- Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush, Character-Aware Neural Language Models, arXiv:1508.06615 [Paper]
- LSTM
- Wojciech Zaremba, Ilya Sutskever, Oriol Vinyal, Recurrent Neural Network Regularization, arXiv:1409.2329 [Paper]
- RNN & LSTM
- Wojciech Zaremba, Ilya Sutskever, Learning to Execute, arXiv:1410.4615 [Paper]
- Grid LSTM
- (#) Nal Kalchbrenner, Ivo Danihelka, Alex Graves, Grid Long Short-Term Memory, arXiv:1507.01526, [Paper]
- Recurrent Visual Attention Model
- (#) Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu, Recurrent Models of Visual Attention, NIPS 2014 [Paper]
- LSTM, GRU, RNN for character-level language (char-rnn)
- Crepe (Character-level Convolutional Networks for Text Classification)
- Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification, NIPS 2015 [Paper]
- Neural Style, Neural Art
- (#) Leon A. Gatys, Alexander S. Ecker, Matthias Bethge, A Neural Algorithm of Artistic Style, arXiv:1508.06576 [Paper]
- Overfeat
- (#) Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus, Yann LeCun, OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks, arXiv:1312.6229 [Paper]
- Alexnet, Overfeat, VGG in Torch on multiple GPUs over ImageNet
- Neural Attention Model for Abstractive Summarization
- Alexander M. Rush, Sumit Chopra, Jason Weston, A Neural Attention Model for Abstractive Summarization, EMNLP 2015 [Paper]
- Memory Networks
- Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus, End-To-End Memory Networks, arXiv:1503.08895, [Paper]
- Neural Turing Machine
- Alex Graves, Greg Wayne, Ivo Danihelka, Neural Turing Machines, arXiv:1410.5401 [Paper]
- Deep Q-network, DeepMind-Atari-Deep-Q-Learner
- Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis, Human-Level Control through Deep Reinforcement Learning, Nature, [Paper]
- TripletNet
- (#) Elad Hoffer, Nir Ailon, Deep metric learning using Triplet network, arXiv:1412.6622 [Paper]
- Word2Vec
- (#) Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean, Efficient Estimation of Word Representations in Vector Space, ICLR 2013 [Paper]
- nn : an easy and modular way to build and train simple or complex neural networks [Code] [Documentation]
- dp : a deep learning library designed for streamlining research and development [Code] [Documentation]
- nngraph : provides graphical computation for nn library [Code] [Oxford Introduction]
- cudnn : Torch FFI bindings for NVIDIA CuDNN [Code]
- rnn : Recurrent Neural Network library [Code]
- fbcunn : Facebook's extensions to torch/cunn [Code] [Documentation]
- fblualib : Facebook libraries and utilities for Lua [Code]
- loadcaffe : Load Caffe networks in Torch [Code]
- iTorch : IPython kernel for Torch with visualization and plotting [Code]
- torch-android : Torch for Android [Code]