J.L. van Hemmen
J.L. van Hemmen
Professor of Theoretical Biophysics, TU München
Verified email at tum.de
Title
Cited by
Cited by
Year
A neuronal learning rule for sub-millisecond temporal coding
W Gerstner, R Kempter, JL Van Hemmen, H Wagner
Nature 383 (6595), 76-78, 1996
10971996
Hebbian learning and spiking neurons
R Kempter, W Gerstner, JL Van Hemmen
Physical Review E 59 (4), 4498, 1999
6041999
Reduction of the Hodgkin-Huxley equations to a single-variable threshold model
WM Kistler, W Gerstner, JL Hemmen
Neural computation 9 (5), 1015-1045, 1997
3841997
Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns
W Gerstner, R Ritz, JL Van Hemmen
Biological cybernetics 69 (5-6), 503-515, 1993
3011993
What matters in neuronal locking?
W Gerstner, JL Van Hemmen, JD Cowan
Neural computation 8 (8), 1653-1676, 1996
2681996
Associative memory in a network of ‘spiking’neurons
W Gerstner, JL van Hemmen
Network: Computation in Neural Systems 3 (2), 139-164, 1992
2611992
Intrinsic stabilization of output rates by spike-based Hebbian learning
R Kempter, W Gerstner, JL Hemmen
Neural computation 13 (12), 2709-2741, 2001
2062001
Classical spin-glass model
JL van Hemmen
Physical Review Letters 49 (6), 409, 1982
2041982
Models of neural networks I
E Domany, JL van Hemmen, K Schulten
Springer Science & Business Media, 2012
2002012
Tunnelling of quantum spins
JL van Hemmen, A Sütö
EPL (Europhysics Letters) 1 (10), 481, 1986
1781986
The replica method and solvable spin glass model
JL Van Hemmen, RG Palmer
Journal of Physics A: Mathematical and General 12 (4), 563, 1979
1511979
Tunneling of quantum spins
JL Van Hemmen, A Sütö
Physica B+ C 141 (1), 37-75, 1986
1501986
Modeling synaptic plasticity in conjunction with the timing of pre-and postsynaptic action potentials
WM Kistler, JL Hemmen
Neural Computation 12 (2), 385-405, 2000
1482000
Coherence and incoherence in a globally coupled ensemble of pulse-emitting units
W Gerstner, JL van Hemmen
Physical review letters 71 (3), 312, 1993
1391993
Lyapunov function for the Kuramoto model of nonlinearly coupled oscillators
JL Van Hemmen, WF Wreszinski
Journal of Statistical Physics 72 (1-2), 145-166, 1993
1381993
Hebbian learning reconsidered: Representation of static and dynamic objects in associative neural nets
A Herz, B Sulzer, R Kühn, JL Van Hemmen
Biological cybernetics 60 (6), 457-467, 1989
1371989
A biologically motivated and analytically soluble model of collective oscillations in the cortex
W Gerstner, R Ritz, JL van Hemmen
Biological cybernetics 68 (4), 363-374, 1993
1361993
Accelerating backpropagation through dynamic self-adaptation
R Solomon, JL Van Hemmen
Neural Networks 9 (4), 589-601, 1996
1231996
Nonlinear neural networks
JL van Hemmen, R Kühn
Physical review letters 57 (7), 913, 1986
121*1986
Temporal sequences and chaos in neural nets
U Riedel, R Kühn, JL Van Hemmen
Physical review A 38 (2), 1105, 1988
1191988
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