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Reimer Kühn
Reimer Kühn
Professor of Statistical Physics, King's College London
Verified email at kcl.ac.uk - Homepage
Title
Cited by
Cited by
Year
Theory of neural information processing systems
ACC Coolen, R Kühn, P Sollich
OUP Oxford, 2005
2552005
Cavity approach to the spectral density of sparse symmetric random matrices
T Rogers, IP Castillo, R Kühn, K Takeda
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 78 (3 …, 2008
1722008
Spectra of sparse random matrices
R Kühn
Journal of Physics A: Mathematical and Theoretical 41 (29), 295002, 2008
1652008
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, 457-467, 1989
1471989
Temporal sequences and chaos in neural nets
U Riedel, R Kühn, JL Van Hemmen
Physical review A 38 (2), 1105, 1988
1301988
Nonlinear neural networks
JL van Hemmen, R Kühn
Physical review letters 57 (7), 913, 1986
1211986
Functional correlation approach to operational risk in banking organizations
R Kühn, P Neu
Physica A: Statistical Mechanics and its Applications 322, 650-666, 2003
1182003
Critical behavior of the randomly spin diluted 2D Ising model: A grand ensemble approach
R Kühn
Physical review letters 73 (16), 2268, 1994
801994
Non-equilibrium dynamics of simple spherical spin models
W Zippold, R Kühn, H Horner
The European Physical Journal B-Condensed Matter and Complex Systems 13, 531-537, 2000
782000
Statistical mechanics for networks of graded-response neurons
R Kühn, S Bös, JL van Hemmen
Physical Review A 43 (4), 2084, 1991
761991
Collective phenomena in neural networks
JL van Hemmen, R Kühn
Models of Neural Networks I, 1-113, 1995
73*1995
Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data
AE Teschendorff, P Sollich, R Kuehn
Methods 67 (3), 282-293, 2014
702014
Forgetful memories
JL van Hemmen, G Keller, R Kühn
EPL (Europhysics Letters) 5 (7), 663, 1988
671988
Increased signaling entropy in cancer requires the scale-free property of protein interaction networks
AE Teschendorff, CRS Banerji, S Severini, R Kuehn, P Sollich
Scientific reports 5, 9646, 2015
652015
Critical behavior of the two-dimensional spin-diluted Ising model via the equilibrium ensemble approach
G Mazzeo, R Kühn
Physical Review E 60 (4), 3823, 1999
651999
The Hebb rule: Representation of static and dynamic objects in neural nets
AVM Herz, B Sulzer, R Kühn, JL Van Hemmen
Europhys. Lett 7, 663-669, 1988
541988
Credit risk enhancement in a network of interdependent firms
P Neu, R Kühn
Physica A: Statistical Mechanics and its Applications 342 (3-4), 639-655, 2004
522004
The Hebb rule: Storing static and dynamic objects in an associative neural network
A Herz, B Sulzer, R Kühn, JL Van Hemmen
EPL (Europhysics Letters) 7 (7), 663, 1988
521988
Analytical results for the distribution of shortest path lengths in random networks
E Katzav, M Nitzan, D ben-Avraham, PL Krapivsky, R Kühn, N Ross, ...
EPL (Europhysics Letters) 111 (2), 26006, 2015
502015
Increasing the efficiency of a neural network through unlearning
JL Van Hemmen, LB Ioffe, R Kühn, M Vaas
Physica A: Statistical Mechanics and its Applications 163 (1), 386-392, 1990
481990
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