Although it is sad that DeepMind moves to Tensorflow, it is not surprising at all. Google team uses Google stuff. However, it is not likely that facebook will move to tensorflow too, so there is nothing more to worry about. And also a bunch of companies and scholar are still stick to Torch.

There has appeared a bunch of new projects based on Torch in recent months. I believe Torch is gathering more and more favor.

I have also updated my awesome torch, here is what I added.

  • Deeper LSTM+ normalized CNN for Visual Question Answering
    • Aishwarya Agrawal, Jiasen Lu, Stanislaw Antol, Margaret Mitchell, C. Lawrence Zitnick, Dhruv Batra, Devi Parikh, VQA: Visual Question Answering, arXiv:1505.00468, [Paper]
  • CTCSpeechRecognition
    • Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu, Deep Speech 2: End-to-End Speech Recognition in English and Mandarin, arXiv:1512.02595, [Paper]
  • Generating Images from Captions with Attention
    • Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov, Generating Images from Captions with Attention, arXiv:1511.02793, [Paper]
  • DenseCap
    • Justin Johnson, Andrej Karpathy, Li Fei-Fei, DenseCap: Fully Convolutional Localization Networks for Dense Captioning, arXiv:1511.07571, [Paper]
  • Sequence-to-Sequence Learning with Attentional Neural Networks
    • (#) Minh-Thang Luong, Hieu Pham, Christopher D. Manning, Effective Approaches to Attention-based Neural Machine Translation, arXiv:1508.04025, [Paper]
  • Artistic style transfer for videos
    • Manuel Ruder, Alexey Dosovitskiy, Thomas Brox Artistic style transfer for videos, arXiv:1604.08610 [Paper]
  • Deep Networks with Stochastic Depth
    • Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger, Deep Networks with Stochastic Depth, arXiv:1603.09382, [Paper]
  • Sentence Convolution Code in Torch
    • (#) Yoon Kim, Convolutional Neural Networks for Sentence Classification, arXiv:1408.5882, [Paper]
  • MGANs
    • Chuan Li, Michael Wand, Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks, arXiv:1604.04382, [Paper] Face Recognition and Clustering*, CVPR 2015 [Paper]
  • Deep Attention Recurrent Q-Network
    • (#) Ivan Sorokin, Alexey Seleznev, Mikhail Pavlov, Aleksandr Fedorov, Anastasiia Ignateva, Deep Attention Recurrent Q-Network, arXiv:1512.01693, [Paper]
  • Let there be Color!: Automatic Colorization of Grayscale Images
    • Satoshi Iizuka, Edgar Simo-Serra, Hiroshi Ishikawa, Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification, SIGGRAPH 2016, [Paper]
  • Context Encoders: Feature Learning by Inpainting
    • Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, Alexei A. Efros, Context Encoders: Feature Learning by Inpainting, CVPR 2016, [Paper]