-
1
-
-
0028392483
-
Learning long-term dependencies with gradient descent is difficult
-
Bengio, Y, Simard, P, and Frasconi, P (1994). "Learning long-term dependencies with gradient descent is difficult." IEEE Trans. Neural Netw. 5(2), 157-166.
-
(1994)
IEEE Trans. Neural Netw
, vol.5
, Issue.2
, pp. 157-166
-
-
Bengio, Y.1
Simard, P.2
Frasconi, P.3
-
2
-
-
2942552269
-
Real-time computation at the edge of chaos in recurrent neural networks
-
Bertschinger, N, and Natschläger, T (2004). "Real-time computation at the edge of chaos in recurrent neural networks." Neural Comput. 16(7), 1413-1436.
-
(2004)
Neural Comput
, vol.16
, Issue.7
, pp. 1413-1436
-
-
Bertschinger, N.1
Natschläger, T.2
-
3
-
-
0345491834
-
Long-term plasticity of intrinsic excitability: Learning rules and mechanisms
-
Daoudal, G, and Debanne, D (2003). "Long-term plasticity of intrinsic excitability: learning rules and mechanisms." Learn. Memory 10, 456-465.
-
(2003)
Learn. Memory
, vol.10
, pp. 456-465
-
-
Daoudal, G.1
Debanne, D.2
-
4
-
-
84940011474
-
Neocortex
-
5th Ed., Shepard, GM, ed, Oxford University Press, NewYork
-
Douglas, R, Markram, H, and Martin, K (2004). "Neocortex." The Synaptic Organization of the Brain, 5th Ed., Shepard, GM, ed., pp. 499-558, Oxford University Press, NewYork.
-
(2004)
The Synaptic Organization of the Brain
, pp. 499-558
-
-
Douglas, R.1
Markram, H.2
Martin, K.3
-
5
-
-
0003149091
-
Recurrent networks: Supervised learning
-
Arbib, MA, ed, MIT Press, Cambridge, MA
-
Doya, K (1995). "Recurrent networks: supervised learning." The Handbook of Brain Theory and Neural Networks, Arbib, MA, ed., pp. 796-800, MIT Press, Cambridge, MA.
-
(1995)
The Handbook of Brain Theory and Neural Networks
, pp. 796-800
-
-
Doya, K.1
-
6
-
-
0000929221
-
What is the goal of sensory coding?
-
Field, DJ (1994). "What is the goal of sensory coding?" Neural Comput. 6(4), 559-601.
-
(1994)
Neural Comput
, vol.6
, Issue.4
, pp. 559-601
-
-
Field, D.J.1
-
8
-
-
84890308118
-
Self organizing maps for time series
-
Hammer, B, Micheli, A, Neubauer, N, Sperduti, A, and Strickert, M (2005). "Self organizing maps for time series." Proceedings of WSOM 2005, 115-122.
-
(2005)
Proceedings of WSOM
, vol.2005
, pp. 115-122
-
-
Hammer, B.1
Micheli, A.2
Neubauer, N.3
Sperduti, A.4
Strickert, M.5
-
9
-
-
84887010605
-
Recent advances in efficient learning of recurrent networks
-
Verleysen, M, ed
-
Hammer, B, Schrauwen, B, and Steil, JJ (2009). "Recent advances in efficient learning of recurrent networks." Proceedings of the European Symposium on Artificial Neural Networks (ESANN), Verleysen, M, ed., 213-226.
-
(2009)
Proceedings of the European Symposium on Artificial Neural Networks (ESANN)
, pp. 213-226
-
-
Hammer, B.1
Schrauwen, B.2
Steil, J.J.3
-
11
-
-
0041914606
-
Gradient flow in recurrent nets: The difficulty of learning long-term dependencies
-
Kremer, SC, and Kolen, JF, eds., IEEE, NewYork
-
Hochreiter, S, Bengio, Y, Frasconi, P, and Schmidhuber, J (2001). "Gradient flow in recurrent nets: the difficulty of learning long-term dependencies." A Field Guide to Dynamical Recurrent Neural Networks, Kremer, SC, and Kolen, JF, eds., IEEE, NewYork.
-
(2001)
A Field Guide to Dynamical Recurrent Neural Networks
-
-
Hochreiter, S.1
Bengio, Y.2
Frasconi, P.3
Schmidhuber, J.4
-
13
-
-
0031573117
-
Long short-term memory
-
Hochreiter, S, and Schmidhuber, J (1997b). "Long short-term memory." Neural Comput. 9(8), 1735-1780.
-
(1997)
Neural Comput
, vol.9
, Issue.8
, pp. 1735-1780
-
-
Hochreiter, S.1
Schmidhuber, J.2
-
15
-
-
1842488370
-
-
GMD- German National Research Institute for Computer Science, Technical Report No. 152
-
Jaeger, H (2001b). "Short term memory in echo state networks." GMD- German National Research Institute for Computer Science, Technical Report No. 152.
-
(2001)
Short Term Memory in Echo State Networks
-
-
Jaeger, H.1
-
16
-
-
78349289898
-
Adaptive nonlinear system identification with echo state networks
-
Becker, S, Thrun, S, and Obermayer, K, eds, MIT Press, Cambridge, MA
-
Jaeger, H (2003). "Adaptive nonlinear system identification with echo state networks." Advances in Neural Information Processing Systems 15 (NIPS 2002), Becker, S, Thrun, S, and Obermayer, K, eds., pp. 593-600, MIT Press, Cambridge, MA.
-
(2003)
Advances in Neural Information Processing Systems 15 (NIPS 2002)
, pp. 593-600
-
-
Jaeger, H.1
-
17
-
-
1842421269
-
Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication
-
Jaeger, H, and Haas, H (2004). "Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication." Science 304(5667), 78-80.
-
(2004)
Science
, vol.304
, Issue.5667
, pp. 78-80
-
-
Jaeger, H.1
Haas, H.2
-
18
-
-
84958950708
-
Unsupervised learning in lstm recurrent neural networks
-
G. Dorffner, H. Bischof, and K. Hornik, eds, Springer, New York
-
Klapper-Rybicka, M, Schraudolph, NN, and Schmidhuber, J (2001). "Unsupervised learning in lstm recurrent neural networks." ICANN-Lecture Notes in Computer Science, Vol. 2130, G. Dorffner, H. Bischof, and K. Hornik, eds., pp. 684-691, Springer, New York.
-
(2001)
ICANN-Lecture Notes in Computer Science
, vol.2130
, pp. 684-691
-
-
Klapper-Rybicka, M.1
Schraudolph, N.N.2
Schmidhuber, J.3
-
19
-
-
34249775479
-
Fading memory and time series prediction in recurrent networks with different forms of plasticity
-
Lazar, A, Pipa, G, and Triesch, J (2007). "Fading memory and time series prediction in recurrent networks with different forms of plasticity." Neural Networks 20(3), 312-322.
-
(2007)
Neural Networks
, vol.20
, Issue.3
, pp. 312-322
-
-
Lazar, A.1
Pipa, G.2
Triesch, J.3
-
20
-
-
51949100900
-
-
Jacobs University, Technical Report No. 11, School of Engineering and Science
-
Lukosevicius, M, and Jaeger, H (2007). "Overview of reservoir recipes." Jacobs University, Technical Report No. 11, School of Engineering and Science.
-
(2007)
Overview of Reservoir Recipes
-
-
Lukosevicius, M.1
Jaeger, H.2
-
21
-
-
34249980918
-
Theory of the computational function of microcircuit dynamics
-
Grillner, S, and Graybiel, AM, eds, MIT Press, Cambridge, MA
-
Maass, W, and Markram, H (2006). "Theory of the computational function of microcircuit dynamics." Microcircuits. The Interface Between Neurons and Global Brain Function, Grillner, S, and Graybiel, AM, eds., pp. 371-392, MIT Press, Cambridge, MA.
-
(2006)
Microcircuits. the Interface Between Neurons and Global Brain Function
, pp. 371-392
-
-
Maass, W.1
Markram, H.2
-
22
-
-
0036834701
-
Real-time computing without stable states: A new framework for neural computation based on perturbations
-
Maass, W, Natschläger, T, and Markram, H (2002). "Real-time computing without stable states: a new framework for neural computation based on perturbations." Neural Comput. 14(11), 2531-2560.
-
(2002)
Neural Comput
, vol.14
, Issue.11
, pp. 2531-2560
-
-
Maass, W.1
Natschläger, T.2
Markram, H.3
-
23
-
-
33846023013
-
Analysis and design of echo state networks
-
Ozturk, MC, Xu, D, and Príncipe, JC (2007). "Analysis and design of echo state networks." Neural Comput. 19(1), 111-138.
-
(2007)
Neural Comput
, vol.19
, Issue.1
, pp. 111-138
-
-
Ozturk, M.C.1
Xu, D.2
Príncipe, J.C.3
-
24
-
-
51749120550
-
Reservoir optimization in recurrent neural networks using Kronecker kernels
-
Rad, AA, Jalili, M, and Hasler, M (2008). "Reservoir optimization in recurrent neural networks using Kronecker kernels." Proceedings of the IEEE Int. Symposium on Circuits and Systems, 868-871.
-
(2008)
Proceedings of the IEEE Int. Symposium on Circuits and Systems
, pp. 868-871
-
-
Rad, A.A.1
Jalili, M.2
Hasler, M.3
-
25
-
-
33847649288
-
Training recurrent networks by Evolino
-
Schmidhuber, J, Wierstra, D, Gagliolo, M, and Gomez, F (2007). "Training recurrent networks by Evolino." Neural Comput. 19(3), 757-779.
-
(2007)
Neural Comput
, vol.19
, Issue.3
, pp. 757-779
-
-
Schmidhuber, J.1
Wierstra, D.2
Gagliolo, M.3
Gomez, F.4
-
26
-
-
84880715730
-
Evolino: Hybrid neuroevolution/optimal linear search for sequence learning
-
Edinburgh, L.P. Kaelbling, and A. Saffiotti, eds
-
Schmidhuber, J, Wierstra, D, and Gomez, FJ (2005). "Evolino: hybrid neuroevolution/optimal linear search for sequence learning." Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI), Edinburgh, L.P. Kaelbling, and A. Saffiotti, eds., pp. 853-858.
-
(2005)
Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI)
, pp. 853-858
-
-
Schmidhuber, J.1
Wierstra, D.2
Gomez, F.J.3
-
27
-
-
40649085253
-
Improving reservoirs using intrinsic plasticity
-
Schrauwen, B, Wardermann, M, Verstraeten, D, Steil, JJ, and Stroobandt, D (2008). "Improving reservoirs using intrinsic plasticity." Neurocomputing 71(7-9), 1159-1171.
-
(2008)
Neurocomputing
, vol.71
, Issue.7-9
, pp. 1159-1171
-
-
Schrauwen, B.1
Wardermann, M.2
Verstraeten, D.3
Steil, J.J.4
Stroobandt, D.5
-
28
-
-
0036568669
-
Stereotypy in neocortical microcircuits
-
Silberberg, G, Gupta, A, and Markram, H (2002). "Stereotypy in neocortical microcircuits." Trends Neurosci. 25(5), 227-230.
-
(2002)
Trends Neurosci
, vol.25
, Issue.5
, pp. 227-230
-
-
Silberberg, G.1
Gupta, A.2
Markram, H.3
-
30
-
-
34249811184
-
Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning
-
Steil, JJ (2007). "Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning." Neural Networks 20(3), 353-364.
-
(2007)
Neural Networks
, vol.20
, Issue.3
, pp. 353-364
-
-
Steil, J.J.1
-
31
-
-
33646185004
-
A gradient rule for the plasticity of a neuron's intrinsic excitability
-
Springer, NewYork
-
Triesch, J (2005). "A gradient rule for the plasticity of a neuron's intrinsic excitability." Artificial Neural Networks: Biological Inspirations-ICANN 2005, pp. 65-70, Springer, NewYork.
-
(2005)
Artificial Neural Networks: Biological Inspirations-ICANN 2005
, pp. 65-70
-
-
Triesch, J.1
-
32
-
-
34247243264
-
Synergies between intrinsic and synaptic plasticity mechanisms
-
Triesch, J (2007). "Synergies between intrinsic and synaptic plasticity mechanisms." Neural Comput. 19(4), 885-909.
-
(2007)
Neural Comput
, vol.19
, Issue.4
, pp. 885-909
-
-
Triesch, J.1
-
33
-
-
34249815487
-
An experimental unification of reservoir computing methods
-
Verstraeten, D, Schrauwen, B, D'Haene, M, and Stroobandt, D (2007). "An experimental unification of reservoir computing methods." Neural Networks 20(3), 391-403.
-
(2007)
Neural Networks
, vol.20
, Issue.3
, pp. 391-403
-
-
Verstraeten, D.1
Schrauwen, B.2
D'Haene, M.3
Stroobandt, D.4
-
34
-
-
0025503558
-
Backpropagation through time: What it does and how to do it
-
Werbos, PJ (1990). "Backpropagation through time: what it does and how to do it." Proc. IEEE 78(10), 1550-1560.
-
(1990)
Proc. IEEE
, vol.78
, Issue.10
, pp. 1550-1560
-
-
Werbos, P.J.1
-
35
-
-
2342592517
-
Short-term memory in orthogonal neural networks
-
White, OL, Lee, DD, and Sompolinsky, H (2004). "Short-term memory in orthogonal neural networks." Phys. Rev. Lett., 92(14), 148102.
-
(2004)
Phys. Rev. Lett.
, vol.92
, Issue.14
, pp. 148102
-
-
White, O.L.1
Lee, D.D.2
Sompolinsky, H.3
-
36
-
-
32444434467
-
Modeling systems with internal state using Evolino
-
ACM, NewYork
-
Wierstra, D, Gomez, FJ, and Schmidhuber, J (2005). "Modeling systems with internal state using Evolino." GECCO '05: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 1795-1802, ACM, NewYork.
-
(2005)
GECCO '05: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation
, pp. 1795-1802
-
-
Wierstra, D.1
Gomez, F.J.2
Schmidhuber, J.3
-
37
-
-
0001202594
-
A learning algorithm for continually running fully recurrent neural networks
-
Williams, RJ, and Zipser, D (1989). "A learning algorithm for continually running fully recurrent neural networks." Neural Comput. 1(2), 270-280.
-
(1989)
Neural Comput
, vol.1
, Issue.2
, pp. 270-280
-
-
Williams, R.J.1
Zipser, D.2
-
38
-
-
0242300203
-
The other side of the engram: Experience-driven changes in the neuronal intrinsic excitability
-
Zhang, W, and Linden, DJ (2003). "The other side of the engram: experience-driven changes in the neuronal intrinsic excitability." Nat. Rev. Neurosci. 4, 885-900.
-
(2003)
Nat. Rev. Neurosci.
, vol.4
, pp. 885-900
-
-
Zhang, W.1
Linden, D.J.2
|