Fetching the paper…
Reading the bibliography…
In recent years the field of neuromorphic low-power systems that consume orders of magnitude less power gained significant momentum.
H. Wilson and J. Cowan, “Excitatory and inhibitory interactions in localized populations of model neurons,” Biophysical Journal , vol. 12, pp. 1–23, 1972
1972
Earlier work this paper cites.
J. L. Elman, “Finding structure in time,” Cognitive science , vol. 14, no. 2, pp. 179–211, 1990
1990
Earlier work this paper cites.
P. J. Werbos, “Backpropagation through time: what it does and how to do it,” Proceedings of the IEEE , vol. 78, no. 10, pp. 1550–1560, 1990
1990
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation , vol. 9, no. 8, pp. 1735–1780, 1997
1997
Earlier work this paper cites.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE , vol. 86, no. 11, pp. 2278–2324, 1998
1998
Earlier work this paper cites.
L. Abbott and S. Song, “Asymmetric hebbian learning, spike timing and neural response variability,” in Advances in Neural Information Processing Systems , vol. 11, 1999, pp. 69–75
1999
Earlier work this paper cites.
X. Li and D. Roth, “Learning question classifiers,” in Proceedings of the 19th international conference on Computational linguistics-Volume 1 . Association for Computational Linguistics, 2002, pp. 1–7
2002
Earlier work this paper cites.
V. Krishnan, S. Das, and S. Chakrabarti, “Enhanced answer type inference from questions using sequential models,” in Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing . Association for Computational Linguistics, 2005, pp. 315–322
2005
Earlier work this paper cites.
G. Indiveri, E. Chicca, and R. Douglas, “A VLSI array of low-power spiking neurons and bistable synapses with spike–timing dependent plasticity,” IEEE Transactions on Neural Networks , vol. 17, no. 1, pp. 211–221, Jan 2006. [Online]. Available: http://ncs.ethz.ch/pubs/pdf/Indiveri_etal06.pdf
2006
Earlier work this paper cites.
M. Khan, D. Lester, L. Plana, A. Rast, X. Jin, E. Painkras, and S. Furber, “Spinnaker: mapping neural networks onto a massively-parallel chip multiprocessor,” in Neural Networks, 2008. IJCNN 2008.(IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on . IEEE, 2008, pp. 2849–2856
2008
Earlier work this paper cites.
Z. Huang, M. Thint, and Z. Qin, “Question classification using head words and their hypernyms,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, 2008, pp. 927–936
2008
Earlier work this paper cites.
D. C. Ciresan, U. Meier, L. M. Gambardella, and J. Schmidhuber, “Deep, big, simple neural nets for handwritten digit recognition,” Neural Computation , vol. 22, no. 12, pp. 3207–3220, 2010
2010
Earlier work this paper cites.
J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio, “Theano: a CPU and GPU math expression compiler,” in Proceedings of the Python for Scientific Computing Conference (SciPy) , vol. 4, 2010
2010
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Proc. of NIPS , 2012, pp. 1097–1105
2012
Earlier work this paper cites.
2012
Earlier work this paper cites.
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, “OverFeat: Integrated recognition, localization and detection using convolutional networks,” arXiv preprint , vol. 312.6229, 2013
2013
Earlier work this paper cites.
L. Deng, G. Hinton, and B. Kingsbury, “New types of deep neural network learning for speech recognition and related applications: An overview,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on . IEEE, 2013, pp. 8599–8603
2013
Earlier work this paper cites.
2013
Cited alongside, same era.
M. D. Zeiler, M. Ranzato, R. Monga, M. Mao, K. Yang, Q. V. Le, P. Nguyen, A. Senior, V. Vanhoucke, J. Dean et al. , “On rectified linear units for speech processing,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on . IEEE, 2013, pp. 3517–3521
2013
Cited alongside, same era.
A. S. Cassidy, P. Merolla, J. V. Arthur, S. K. Esser, B. Jackson, R. Alvarez-icaza, P. Datta, J. Sawada, T. M. Wong, V. Feldman, A. Amir, D. B. dayan Rubin, E. Mcquinn, W. P. Risk, and D. S. Modha, “Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores,” in in International Joint Conference on Neural Networks (IJCNN). IEEE , 2013
2013
Cited alongside, same era.
S. Habenschuss, Z. Jonke, and W. Maass, “Stochastic computations in cortical microcircuit models,” PLoS computational biology , vol. 9, no. 11, p. e1003311, 2013
S. Hussain, A. Basu, R. M. Wang, and T. J. Hamilton, “Delay learning architectures for memory and classification,” Neurocomputing , vol. 138, pp. 14–26, 2014
2014
Later among the works it cites.
2014
Later among the works it cites.
2014
Later among the works it cites.
V. Mnih, N. Heess, A. Graves et al. , “Recurrent models of visual attention,” in Advances in Neural Information Processing Systems , 2014, pp. 2204–2212
2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2013
Cited alongside, same era.
E. Neftci, S. Das, B. Pedroni, K. Kreutz-Delgado, and G. Cauwenberghs, “Restricted boltzmann machines and continuous-time contrastive divergence in spiking neuromorphic systems,” May 2013
2013
Cited alongside, same era.
A. Graves, A.-r. Mohamed, and G. Hinton, “Speech recognition with deep recurrent neural networks,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on . IEEE, 2013, pp. 6645–6649
2013
Cited alongside, same era.
N. Boulanger-Lewandowski, Y. Bengio, and P. Vincent, “Audio chord recognition with recurrent neural networks.” in ISMIR , 2013, pp. 335–340
2013
Cited alongside, same era.
P. A. Merolla, J. V. Arthur, R. Alvarez-Icaza, A. S. Cassidy, J. Sawada, F. Akopyan, B. L. Jackson, N. Imam, C. Guo, Y. Nakamura et al. , “A million spiking-neuron integrated circuit with a scalable communication network and interface,” Science , vol. 345, no. 6197, pp. 668–673, 2014
2014
Cited alongside, same era.
B. V. Benjamin, P. Gao, E. McQuinn, S. Choudhary, A. R. Chandrasekaran, J. Bussat, R. Alvarez-Icaza, J. V. Arthur, P. Merolla, and K. Boahen, “Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations,” Proceedings of the IEEE , vol. 102, no. 5, pp. 699–716, 2014
2014
Cited alongside, same era.
N. Kalchbrenner, E. Grefenstette, and P. Blunsom, “A convolutional neural network for modelling sentences,” Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics , June 2014. [Online]. Available: http://goo.gl/EsQCuC
2014
Cited alongside, same era.
2014
Cited alongside, same era.
2014
Cited alongside, same era.
P. U. Diehl, D. Neil, J. Binas, M. Cook, S.-C. Liu, and M. Pfeiffer, “Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing,” in International Joint Conference on Neural Networks (IJCNN), . IEEE, 2015, pp. 1–8
2015
Later among the works it cites.
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan, “Show and tell: A neural image caption generator,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2015
2015
Later among the works it cites.
G. Zarrella, J. Henderson, E. M. Merkhofer, and L. Strickhart, “Mitre: Seven systems for semantic similarity in tweets,” Proceedings of SemEval , 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
E. Stromatias, D. Neil, M. Pfeiffer, F. Galluppi, S. B. Furber, and S.-C. Liu, “Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms,” Frontiers in neuroscience , vol. 9, 2015
2015
Later among the works it cites.
S. K. Esser, R. Appuswamy, P. Merolla, J. V. Arthur, and D. S. Modha, “Backpropagation for energy-efficient neuromorphic computing,” in Advances in Neural Information Processing Systems , 2015, pp. 1117–1125
2015
Later among the works it cites.
Y. Li, L. Xu, F. Tian, L. Jiang, X. Zhong, and E. Chen, “Word embedding revisited: A new representation learning and explicit matrix factorization perspective,” 2015
2015
Later among the works it cites.
J. Schmidhuber, “Deep learning in neural networks: An overview,” Neural Networks , vol. 61, pp. 85–117, 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
P. U. Diehl and M. Cook, “Unsupervised learning of digit recognition using spike-timing-dependent plasticity,” Frontiers in Computational Neuroscience , vol. 9, p. 99, 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
P. U. Diehl, B. Pedroni, A. Cassidy, P. Merolla, E. Neftci, and G. Zarrella, “Truehappiness: Sentiment analysis on truenorth,” arXiv , 2016
2016
Closest in time.