Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
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[1] Barak A. Pearlmutter. Learning State Space Trajectories in Recurrent Neural Networks , 1989, Neural Computation.
[2] Yuichi Nakamura,et al. Approximation of dynamical systems by continuous time recurrent neural networks , 1993, Neural Networks.
[3] Gert Cauwenberghs,et al. An analog VLSI recurrent neural network learning a continuous-time trajectory , 1996, IEEE Trans. Neural Networks.
[4] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[5] Jürgen Schmidhuber,et al. Recurrent nets that time and count , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[6] Jon Barker,et al. An audio-visual corpus for speech perception and automatic speech recognition. , 2006, The Journal of the Acoustical Society of America.
[7] A. Pérez-Villalba. Rhythms of the Brain, G. Buzsáki. Oxford University Press, Madison Avenue, New York (2006), Price: GB £42.00, p. 448, ISBN: 0-19-530106-4 , 2008 .
[8] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[9] Wolfgang Maass,et al. Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity , 2013, PLoS Comput. Biol..
[10] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[11] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[12] Tobi Delbruck,et al. Real-time classification and sensor fusion with a spiking deep belief network , 2013, Front. Neurosci..
[13] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[14] Erich Elsen,et al. Deep Speech: Scaling up end-to-end speech recognition , 2014, ArXiv.
[15] Jürgen Schmidhuber,et al. A Clockwork RNN , 2014, ICML.
[16] Tobi Delbrück,et al. Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output , 2014, Proceedings of the IEEE.
[17] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[18] Colin Raffel,et al. Lasagne: First release. , 2015 .
[19] Yoshua Bengio,et al. Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks , 2015, IEEE Transactions on Multimedia.
[20] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[21] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[22] Gregory Cohen,et al. Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades , 2015, Front. Neurosci..
[23] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[24] Shih-Chii Liu,et al. Effective sensor fusion with event-based sensors and deep network architectures , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).
[25] Jürgen Schmidhuber,et al. Lipreading with long short-term memory , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[26] Garrick Orchard,et al. Skimming Digits: Neuromorphic Classification of Spike-Encoded Images , 2016, Front. Neurosci..
[27] Erhardt Barth,et al. Recurrent Dropout without Memory Loss , 2016, COLING.