Publications

Found 146 results
Author Title [ Year(Asc)]
Golomb D, Hansel D, Shraiman B, Sompolinsky H.  1992.  Clustering in globally coupled phase oscillators. Physical Review. A. 45:3516–3530.
Tsodyks M., Sompolinsky H.  1992.  Processing of Sensory Information by a Network of Oscillators with Memory.. International Journal of Neural Systems 3, 51..
Seung HS, Opper M.A., Sompolinsky H.  1992.  Query by Committee.. in Proceedings of the Fifth Annual Workshop on Computational Learning Theory, Warmuth M.K. and Valiant L.G., editors. (Kaufmann, San Mateo, CA), p. 287..
Aranson I, Golomb D, Sompolinsky H.  1992.  Spatial coherence and temporal chaos in macroscopic systems with asymmetrical couplings. Physical Review Letters. 68:3495–3498.
Seung HS, Sompolinsky H, Tishby N.  1992.  Statistical mechanics of learning from examples. Physical Review. A. 45:6056–6091.
Hansel D, Sompolinsky H.  1992.  Synchronization and computation in a chaotic neural network. Physical Review Letters. 68:718–721.
Sompolinsky H, Golomb D, Golomb D.  1991.  Cooperative dynamics in visual processing. Physical Review. A. 43:6990–7011.
Sompolinsky H, , .  1991.  Phase Coherence and Computation in a Neural Network of Coupled Oscillators. Non-Linear Dynamics and Neural Networks, Schuster H.G and Singer W, Eds. (VCH, Weinheim, 1991), pp. 113-140..
Kleinfeld D, Chiel HJ, Sompolinsky H.  1991.  Small Nervous Systems and Neural Network Models. Non-Linear Dynamics and Neural Networks, Schuster H.G and Singer W, Eds. (VCH, Weinheim, 1991), pp. 77-109..
Sompolinsky H, Golomb D, Kleinfeld D.  1990.  Global processing of visual stimuli in a neural network of coupled oscillators. Proceedings of the National Academy of Sciences of the United States of America. 87:7200–7204.
Hansel D, Sompolinsky H.  1990.  Learning from Examples in a Single-Layer Neural Network.. Europhysics Letters 11, 687..
Sompolinsky H, Tishby N, S SH.  1990.  Learning from examples in large neural networks. Physical Review Letters. 65:1683–1686.
Sompolinsky H, Tishby N.  1990.  Learning in a Two-Layer Neural Network of Edge Detectors.. Europhysics Letters 13, 567..
Barkai E, Kanter I, Sompolinsky H.  1990.  Properties of sparsely connected excitatory neural networks. Physical Review. A. 41:590–597.
Golomb D, Rubin N, Sompolinsky H.  1990.  Willshaw model: Associative memory with sparse coding and low firing rates. Physical Review. A. 41:1843–1854.
Kleinfeld D, Sompolinsky H.  1989.  Associative Network Models for Central Pattern Generators. Methods in Neuronal Modeling: From Synapse to Networks, Koch C and Segev I, Eds., Ch. 7 (MIT Press, Cambridge, MA 1989). pp. 195-246..
Rubin N, Sompolinsky H.  1989.  Neural Networks with Low Local Firing Rates. Europhysics Letters 10, 465..
Yacoby ER, Wolfus Y, Yeshurun Y, Felner I, Sompolinsky H.  1989.  Scaling of the irreversible magnetization curves of YBaCuO. Physica C: Superconductivity. 162–164(1)
Wolfus Y, Yeshurun Y, Felner I, Sompolinsky H.  1989.  Scaling properties of the irreversible magnetization curves of high-temperature superconductors. Physical Review. B, Condensed Matter. 40:2701–2703.
Kanter I, Sompolinsky H.  1987.  Associative recall of memory without errors. Physical Review. A. 35:380–392.

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