Temporal-Kernel Recurrent Neural Networks

[1]  Peter Dayan,et al.  Encoding and Decoding Spikes for Dynamic Stimuli , 2008, Neural Computation.

[2]  Jürgen Schmidhuber,et al.  A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Matthew M Botvinick,et al.  Short-term memory for serial order: a recurrent neural network model. , 2006, Psychological review.

[4]  Harald Haas,et al.  Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication , 2004, Science.

[5]  Daniel D. Lee,et al.  Short-term memory in orthogonal neural networks. , 2004, Physical review letters.

[6]  Xiao-Jing Wang,et al.  A Model of Visuospatial Working Memory in Prefrontal Cortex: Recurrent Network and Cellular Bistability , 1998, Journal of Computational Neuroscience.

[7]  Danil V. Prokhorov,et al.  Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks , 2003, Neural Networks.

[8]  Jürgen Schmidhuber,et al.  Learning Precise Timing with LSTM Recurrent Networks , 2003, J. Mach. Learn. Res..

[9]  Danil V. Prokhorov,et al.  Adaptive behavior with fixed weights in RNN: an overview , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[10]  Sepp Hochreiter,et al.  Meta-learning with backpropagation , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[11]  Jürgen Schmidhuber,et al.  Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.

[12]  Geoffrey E. Hinton,et al.  Spiking Boltzmann Machines , 1999, NIPS.

[13]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[14]  H S Seung,et al.  How the brain keeps the eyes still. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Peter Tiño,et al.  Learning long-term dependencies in NARX recurrent neural networks , 1996, IEEE Trans. Neural Networks.

[16]  Walter J. Freeman,et al.  The Hebbian paradigm reintegrated: Local reverberations as internal representations , 1995, Behavioral and Brain Sciences.

[17]  Yoshua Bengio,et al.  Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.

[18]  José Carlos Príncipe,et al.  The gamma model--A new neural model for temporal processing , 1992, Neural Networks.

[19]  Ronald J. Williams,et al.  Training recurrent networks using the extended Kalman filter , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[20]  Sepp Hochreiter,et al.  Untersuchungen zu dynamischen neuronalen Netzen , 1991 .

[21]  Paul J. Werbos,et al.  Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.

[22]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[23]  W. Precht.  The synaptic organization of the brain G.M. Shepherd, Oxford University Press (1975). 364 pp., £3.80 (paperback) , 1976, Neuroscience.