bibliography.bib

%Books
@book{neural_nets_deep_learning,
  title = {Neural Networks and Deep Learning},
  publisher = {Determination Press},
  year = {2015},
  author = {Michael A. Nielsen}
}
@book{pattern_and_ml,
  title = {Pattern Recognition and Machine Learning},
  publisher = {Springer Publishing},
  year = {2006},
  author = {Christopher M. Bishop},
  ISBN = 9788132209065
}

% Unpublished Books
@unpublished{deep_learning,
    title={Deep Learning},
    author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
    note={Book in preparation for MIT Press},
    url={http://www.deeplearningbook.org},
    year={2016}
}
@unpublished{conv_guide,
    title={A guide to convolution arithmetic for deep learning},
    author={Vincent Dumoulin and Francesco Visin},
    url={https://arxiv.org/abs/1603.07285},
    day={24},
    month={March},
    year={2016}
}

% Papers
@inproceedings{unsup_learn_lstm,
  author    = {Nitish Srivastava and 
               Elman Mansimov and 
               Ruslan Salakhutdinov},
  title     = {Unsupervised Learning of Video Representations using {LSTM}s},
  booktitle = {ICML},
  year      = {2015}
}
@inproceedings{spat_temp_video_autoenc,
  author    = {Viorica P{\u a}tr{\u a}ucean and
               Ankur Handa and
               Roberto Cipolla},
  title     = {Spatio-temporal video autoencoder with differentiable memory},
  booktitle = {ICLR},
  year      = {2016}
}
@inproceedings{deep_multiscale_video_pred,
  author    = {Michael Mathieu and
               Camille Couprie and
               Yann LeCun},
  title     = {Deep Multi-Scale Video Prediction Beyond Mean Square Error},
  booktitle = {ICLR},
  year      = {2016},
  month     = {February},
}
@inproceedings{conv_lstm_nowcasting,
  author    = {Xingjian Shi and
               Zhourong Chen and
               Hao Wang and
               Dit-Yan Yeung},
  title     = {Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting},
  year      = {2015}
}
@inproceedings{ann,
  author    = {Abhishek Kar},
  title     = {Future Image Prediction using Artificial Neural Networks},
  year      = {2012},
}
@inproceedings{ann2,
  author    = {Nishchal K. Verma},
  title     = {Future Image Frame Generation using Artificial Neural Network with Selected Features},
  booktitle = {AIPR},
  year      = {2012},
  month     = {October},
}
@inproceedings{flownet,
  author    = {Philipp Fischer and
               Alexey Dosovitskiy and
               Philip Häusser and
               Caner Hazırbas and
               Vladimir Golkov},
  title     = {FlowNet: Learning Optical Flow with Convolutional Networks},
  year      = {2015},
  url       = {https://arxiv.org/abs/1504.06852}
}
@inproceedings{two_stream_action,
  author    = {Karen Simonyan and Andrew Zisserman},
  title     = {Two-Stream Convolutional Networks for Action Recognition in Videos},
  booktitle = {Proc. NIPS},
  year      = {2014},
  pages     = {568-576}
}
@inproceedings{large_video_class,
  author    = {Andrej Karpathy and 
               George Toderici and 
               Sanketh Shetty and
               Thomas Leung and
               Rahul Sukthankar and
               Li Fei-Fei},
  title     = {Large-scale Video Classification with Convolutional Neural Networks},
  booktitle = {CVPR},
  year      = {2014},
  pages     = {1725-1732}
}
@inproceedings{conv3d_action_class,
  author    = {Shuiwang Ji and 
               Wei Xu and 
               Ming Yang and
               Kai Yu},
  title     = {3D Convolutional Neural Networks for Human Action Recognition},
  booktitle = {IEEE Trans. PAMI},
  year      = {2013},
  pages     = {221-231}
}
@inproceedings{longterm_rec_recog,
  author    = {Jeff Donahue and
               Lisa Anne Hendricks and
               Marcus Rohrbach and
               Subhashini Venugopalan and
               Sergio Guadarrama and
               Kate Saenko and
               Trevor Darrell},
  title     = {Long-term Recurrent Convolutional Networks for Visual Recognition and Description},
  year      = {2014},
}
@inproceedings{lstm,
  author    = {Sepp Hochreiter and
               Jürgen Schmidhuber},
  title     = {Long short-term memory},
  booktitle = {Neural Computing},
  year      = {1997},
  pages     = {1735-1780}
}
@inproceedings{lstm_v2,
  author    = {Alex Graves and
               Santiago Fernández and
               Faustino Gomez and
               Jürgen Schmidhuber},
  title     = {Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks},
  booktitle = {ICML},
  year      = {2006},
  pages     = {369-376}
}
@inproceedings{frame_interpol,
  author    = {João Ascenso and
               Catarina Brites and
               Fernando Pereira},
  title     = {Improving Frame Interpolation with Spatial Motion Smoothing for Pixel Domain Distributed Video Coding},
  booktitle = {5th EURASIP Conference on Speech and Image Processing, Multimedia Communications and Services},
  year      = {2005},
  pages     = {1-6}
}
@inproceedings{causal_video_seg,
  author    = {Camille Couprie and
               Clement Farabet and Yann LeCun and
               Laurent Najman},
  title     = {Causal Graph-Based Video Segmentation},
  booktitle = {ICIP},
  year      = {2013},
}
@inproceedings{relu,
  author    = {Xavier Glorot and
               Antoine Bordes and
               Yoshua Bengio},
  title     = {Deep Sparse Rectifier Neural Networks},
  booktitle = {AISTATS},
  year      = {2011},
}
@inproceedings{xavier-init,
  author    = {Xavier Glorot and
               Yoshua Bengio},
  title     = {Understanding the difficulty of training deep feedforward neural networks},
  booktitle = {AISTATS},
  year      = {2010},
}
@inproceedings{adam,
  author    = {Diederik P. Kingma and
               Jimmy Lei Ba},
  title     = {Adam: A Method for Stochasitc Optimization},
  booktitle = {ICLR},
  year      = {2015},
}
@inproceedings{imagenet,
  author    = {Alex Krizhevsky and
               Ilya Sutskever and
               Geoffrey E. Hinton},
  title     = {ImageNet Classification with Deep Convolutional Neural Networks},
  booktitle = {NIPS},
  year      = {2012},
}
@inproceedings{gan,
  author    = {Ian J. Goodfellow and
               Jean Pouget-Abadie and
               Mehdi Mirza and
               Bing Xu and
               David Warde-Farley and
               Sherjil Ozair and
               Aaron Courville and
               Yoshua Bengio},
  title     = {Generativ Adversarial Nets},
  booktitle = {NIPS},
  year      = {2014},
}
@inproceedings{batchnorm,
  author    = {Sergey Ioffe and
               Christian Szegedy},
  title     = {Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift},
  booktitle = {Proc. of IEEE},
  year      = {2015},
}
@inproceedings{rnn-batchnorm,
  author    = {Tim Cooijmans and
               Nicolas Balls and
               César Laurent and
               \c{C}a\u{g}lar Gül\c{c}ehre},
  title     = {Recurrent Batch Normalization},
  booktitle = {Proc. of IEEE},
  year      = {2015},
}
@inproceedings{gru,
  author    = {Junyoung Chung and
               Caglar Gulcehre and
               Kyunghyun Cho and
               Yoshua Bengio},
  title     = {Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling},
  year      = {2014},
}
@inproceedings{lstm-space,
  author    = {Klaus Greff and
               Rupesh Kumar Srivastava and
               Jan Koutnik and
               Bas R. Steunebrink and
               Jürgen Schmidhuber},
  title     = {LSTM: A Search Space Odyssey},
  year      = {2015},
}
@inproceedings{gru-video,
  author    = {Nicolas Ballas and
               Li Yao and
               Chris Pal and
               Aaron Courville},
  title     = {Delving Deeper into Convolutional Networks for Learning Video Representations},
  booktitle = {ICLR},
  year      = {2016},
  month     = {March},
}
@inproceedings{learning-perc-sim,
  author    = {Karl Ridgeway and
               Jake Snell and
               Brett D. Roads and
               Richard S. Zemel and
               Michael C. Mozer},
  title     = {Learning to Generate Images with Perceptual Similarity Metrics},
  year      = {2016},
  month     = {March},
}
@inproceedings{loss-func-img-proc,
  author    = {Hang Zhao and
               Orazio Gallo and
               Iuri Frosio and
               Jan Kautz},
  title     = {Loss Functions for Neural Networks for Image Processing},
  year      = {2016},
  month     = {June},
}
@inproceedings{ms-ssim,
  author    = {Zhou Wang and
               Eero P. Simonselli and
               Alen Conrad Bovik},
  title     = {Multi-Scale Structural Similarity for Image Quality Assessment},
  booktitle = {IEEE Conference on Signals, Systems and Computers},
  year      = {2003},
  month     = {November},
}
@inproceedings{flow-static-img,
  author    = {Jacob Walker and
               Abhinav Gupta and
               Martial Hebert},
  title     = {Dense Optical Flow Prediction from a Static Image},
  year      = {2015},
  month     = {December},
}
@inproceedings{sem-img-inpainting,
  author    = {Raymond Yeh and
               Chen Chen and
               Teck Yian Lim and
               Mark Hasegawa-Johnson and
               Minh N. Do},
  title     = {Semantic Image Inpainting with Perceptual and Contextual Losses},
  year      = {2016},
  month     = {July},
}
@inproceedings{k-sparse-autoenc,
  author    = {Alireza Makhzani and
               Brendan Frey},
  title     = {k-Sparse Autoencoders},
  booktitle = {ICLR},
  year      = {2014},
  month     = {December},
}
@inproceedings{rect-autoenc,
  author    = {Xavier Gloro and
               Antoine Bordes and
               Yoshua Bengio},
  title     = {Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach},
  booktitle = {ICML},
  year      = {2011},
  month     = {June},
}
@inproceedings{rnn-enc-dec1,
  author    = {Xi Peng and
               Rogerio Feris and
               Xiaoyu Wang and
               Dimitris Metaxas},
  title     = {A Recurrent Encoder-Decoder Network for Sequential Face Alignment},
  year      = {2016},
  month     = {August},
}
@inproceedings{rnn-enc-dec2,
  author    = {Liang Lu and
			   Xingxing Zhang and
			   Steve Renals},
  title     = {On Training Recurrent Neural Network Encoder-Decoder For Large Vocabulary End-to-End Speech Recognition},
  booktitle = {ICASSP},
  year      = {2016},
  month     = {March},
}
@inproceedings{beyond_snippets_video_class,
  author    = {Joe Yue-Hei Ng and
               Matthew Hausknecht and
               Sudheendra Vijayanarasimhan and
               Oriol Vinyals and
               Rajat Monga and
               George Toderici},
  title     = {Beyond Short Snippets: Deep Networks for Video Classification},
  booktitle = {CVPR},
  year      = {2016},
}
@inproceedings{brnn_fist,
  author    = {Kyunghyun Cho and
               Bart van Merrienboer and
               Caglar Gulcehre and
               Dzmitry Bahdanau and
               Fethi Bougares and
               Holger. Schwenk and
               Yoshua Bengio},
  title     = {Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation},
  booktitle = {EMNLP},
  year      = {2014},
}
@inproceedings{brnn_second,
  author    = {Ilya Sutskever and
               Oriol Vinyals and
               Quoc V. Le},
  title     = {Sequence to Sequence Learning with Neural Networks},
  booktitle = {NNIPS},
  year      = {2014},
}
@inproceedings{ucf,
  author    = {Khurram Soomro and
               Amir Roshan Zamir and
               Mubarak Shah},
  title     = {UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild},
  booktitle = {CRCV-TR-12-01},
  year      = {2012},
  month     = {November},
}
@inproceedings{gen_img_perc_sim,
  author    = {Alexey Dosovitskiy and
               Thomas Brox},
  title     = {Generating Images with Perceptual Similarity Metrics based on Deep Networks},
  year      = {2016},
  month     = {February},
}
@inproceedings{sched_sample,
  author    = {Samy Bengio and
               Oriol Vinyals and
               Navdeep Jaitly and
               Noam Shazeer},
  title     = {Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks},
  year      = {2015},
  month     = {September},
}

%Journals
@article{lecun_conv,
  author    = {Yann LeCun and
               Léon Bottou and
               Yoshua Bengio and
               Patrick Hafner},
  title     = {Gradient-Based Learning Applied to Document Recognition},
  journal   = {Proceedings of the IEEE},
  volume    = 86,
  number    = 11,
  pages     = {2278-2324},
  year      = {1998},
}
@article{dropout,
  author  = {Nitish Srivastava and 
             Geoffrey E. Hinton and
             Alex Krizhevsky and
             Ilya Sutskever and
             Ruslan R. Salakhutdinov}, 
  title   = {Dropout: A Simple Way to Prevent Neural Networks from Overfitting},
  journal = {Journal of Machine Learning Research},
  year    = 2014,
  number  = 15,
  pages   = {1929-1958},
  month   = 6,
}
@article{rnn-vanish,
  author  = {Yoshua Bengio and
             Patrice Simard and
             Paolo Frasoni},
  title   = {Learning Long-Term Dependencies with Gradient Descent is Difficult},
  journal = {IEEE Transaction on Neural Networks},
  year    = {1994},
  volume  = 5,
  number  = 2,
  pages   = {157-166},
  month   = {March},
}
@article{lstm_peep,
  author  = {Felix A. Gers and
             Jürgen Schmidhuber},
  title   = {Recurrent Nets that Time and Count},
  journal = {IEEE Trans. on Neural Networks},
  year    = {2000},
  volume  = 3,
  pages   = {850-855},
  isbn    = {0769506194},
}
@article{ssim,
  author    = {Zhou Wang and
               Alen Conrad Bovik and
               Hamid Rahim Sheikh and
               Eero P. Simoncelli},
  title     = {Image Quality Assessment: From Error Visibility to Structural Similarity},
  journal   = {IEEE Trans. Image Processing},
  volume    = {13},
  number    = {4},
  year      = {2004},
  month     = {April},
  pages     = {600-612}
}
@article{ssim-slide,
  author    = {Zhou Wang and
               Alen Conrad Bovik},
  title     = {A Univeral Image Quality Index},
  journal   = {IEEE Signal Processing Letters},
  volume    = {9},
  year      = {2002},
  month     = {March},
  pages     = {81-84}
}
@article{autoenc_deeper,
  author    = {Geoffrey E. Hinton and
               Ruslan R. Salakhutdinov},
  title     = {Reducing the Dimensionality of data with Neural Networks},
  journal   = {Sience},
  volume    = {313},
  number    = {5786},
  year      = {2006},
  month     = {July},
  pages     = {504-507}
}

%Thesis
@mastersthesis{hochreiter,
  author       = {Josef Hochreiter}, 
  title        = {Untersuchungen zu dynamischen neuronalen Netzen},
  school       = {Technische Universität Munchen},
  day          = {15},
  month        = {June},
  year         = {1991},
  address      = {Arcisstr. 21, 80333 Munich , Germany},
}


% Websites
@online{understand_lstm,
  author = {Christopher Olah},
  title = {Understanding LSTM Networks},
  day = 27,
  month = August,
  year = 2015,
  url = {http://colah.github.io/posts/2015-08-Understanding-LSTMs},
  urldate = {2016-09-20}
}
@online{understand_xavier,
  author = {Andreas L. Jone},
  title = {An Explanation of Xavier Initialization},
  day = 14,
  month = February,
  year = 2015,
  url = {http://andyljones.tumblr.com/post/110998971763/an-explanation-of-xavier-initialization},
  urldate = {2016-09-22}
}
@online{optimization,
  author = {Sebastian Ruder},
  title = {An overview of gradient descent optimization algorithms},
  day = 19,
  month = January,
  year = 2016,
  url = {http://sebastianruder.com/optimizing-gradient-descent},
  urldate = {2016-09-22}
}
@online{rnn-effectiveness,
  author = {Andrej Karpathy},
  title = {The Unreasonable Effectiveness of Recurrent Neural Networks},
  day = 11,
  month = May,
  year = 2015,
  url = {http://karpathy.github.io/2015/05/21/rnn-effectiveness},
  urldate = {2016-09-25}
}
@online{rnn-bptt,
  author = {Geoffrey Hinton},
  title = {Neural Networks for Machine Learning: Training RNNs with Back Propagation},
  day = 6,
  month = November,
  year = 2013,
  url = {https://www.coursera.org/learn/neural-networks},
  urldate = {2016-09-25}
}
@online{stanford_data_pre,
  author = {Andrew Ng and
            Jiquan Ngiam and
            Chuan Yu Foo and
            Yifan Mai and
            Caroline Suen},
  title = {Standford: Unsupervised Feature Learning and Deep Learning},
  day = 8,
  month = April,
  year = 2013,
  url = {http://ufldl.stanford.edu/wiki/index.php/Data_Preprocessing},
  urldate = {2016-10-03}
}

@online{tf_impl_gan,
  author = {Matt Cooper},
  title = {Adversarial Video Generation},
  day = 9,
  month = September,
  year = 2016,
  url = {https://github.com/dyelax/Adversarial_Video_Generation},
  urldate = {2016-10-14}
}



%other
@misc{tensorflow2015-whitepaper,
title={{TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={http://tensorflow.org/},
note={Software available from tensorflow.org},
author={
    Martin Abadi and
    Ashish Agarwal and
    Paul Barham and
    Eugene Brevdo and
    Zhifeng Chen and
    Craig Citro and
    Greg S. Corrado and
    Andy Davis and
    Jeffrey Dean and
    Matthieu Devin and
    Sanjay Ghemawat and
    Ian Goodfellow and
    Andrew Harp and
    Geoffrey Irving and
    Michael Isard and
    Yangqing Jia and
    Rafal Jozefowicz and
    Lukasz Kaiser and
    Manjunath Kudlur and
    Josh Levenberg and
    Dan Mane and
    Rajat Monga and
    Sherry Moore and
    Derek Murray and
    Chris Olah and
    Mike Schuster and
    Jonathon Shlens and
    Benoit Steiner and
    Ilya Sutskever and
    Kunal Talwar and
    Paul Tucker and
    Vincent Vanhoucke and
    Vijay Vasudevan and
    Fernanda Viegas and
    Oriol Vinyals and
    Pete Warden and
    Martin Wattenberg and
    Martin Wicke and
    Yuan Yu and
    Xiaoqiang Zheng},
  year={2015},
}
@inproceedings{distbelief,
title = {Large Scale Distributed Deep Networks},
author  = {Jeffrey Dean and Greg S. Corrado and Rajat Monga and Kai Chen and Matthieu Devin and Quoc V. Le and Mark Z. Mao and Marc'Aurelio Ranzato and Andrew Senior and Paul Tucker and Ke Yang and Andrew Y. Ng},
year  = 2012,
booktitle = {NIPS}
}

% REPORTS
@techreport{deep_arch_ai,
     title = {{Learning Deep Architectures for AI}},
     author = {Yoshua Bengio},
     group = {Dept. IRO},
     year = {2008},
     institution = {Université de Montréal},
     month = {July},
     url = {http://www.iro.umontreal.ca/~lisa/pointeurs/TR1312.pdf},
}