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Wulfram Gerstner: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Silvio Borer, Wulfram Gerstner
    Support Vector Representation of Multi-categorical Data. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:733-738 [Conf]
  2. Renaud Jolivet, Timothy J. Lewis, Wulfram Gerstner
    The Spike Response Model: A Framework to Predict Neuronal Spike Trains. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:846-853 [Conf]
  3. Julien Mayor, Wulfram Gerstner
    Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:839-845 [Conf]
  4. Jean-Pascal Pfister, David Barber, Wulfram Gerstner
    Optimal Hebbian Learning: A Probabilistic Point of View. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:92-98 [Conf]
  5. Pierre-Edouard Sottas, Wulfram Gerstner
    Dynamic Noise Annealing for Learning Temporal Sequences with Recurrent Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:1144-1149 [Conf]
  6. Thomas Strösslin, Ricardo Chavarriaga, Denis Sheynikhovich, Wulfram Gerstner
    Modelling Path Integrator Recalibration Using Hippocampal Place Cells. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:51-56 [Conf]
  7. Thomas Strösslin, Christophe Krebser, Angelo Arleo, Wulfram Gerstner
    Combining Multimodal Sensory Input for Spatial Learning. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:87-92 [Conf]
  8. Jiri Matas, Miroslav Hamouz, Kenneth Jonsson, Josef Kittler, Yongping Li, Constantine Kotropoulos, Anastasios Tefas, Ioannis Pitas, Teewoon Tan, Hong Yan, Fabrizio Smeraldi, N. Capdevielle, Wulfram Gerstner, Yousri Abdeljaoued, Josef Bigün, S. Ben-Yacoub, E. Mayoraz
    Comparison of Face Verification Results on the XM2VTS Database. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:4858-4863 [Conf]
  9. José del R. Millán, Frédéric Renkens, Josep Mouriño, Wulfram Gerstner
    Non-Invasive Brain-Actuated Control of a Mobile Robot. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2003, pp:1121-1126 [Conf]
  10. Mona Spiridon, Wulfram Gerstner
    Noise Modulation by Stochastic Neurons of the Integrate-and Fire Type. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 1999, pp:268-276 [Conf]
  11. Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strösslin, Wulfram Gerstner
    Spatial Representation and Navigation in a Bio-inspired Robot. [Citation Graph (0, 0)][DBLP]
    Biomimetic Neural Learning for Intelligent Robots, 2005, pp:245-264 [Conf]
  12. Angelo Arleo, Fabrizio Smeraldi, Stéphane Hug, Wulfram Gerstner
    Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:89-95 [Conf]
  13. Wulfram Gerstner
    Associative Memory in a Network of `Biological' Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:84-90 [Conf]
  14. Wulfram Gerstner, J. Leo van Hemmen
    How to Describe Neuronal Activity: Spikes, Rates, or Assemblies? [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:463-470 [Conf]
  15. Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner
    Integrate-and-Fire models with adaptation are good enough. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  16. Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen
    Spike-Based Compared to Rate-Based Hebbian Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:125-131 [Conf]
  17. Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen, Hermann Wagner
    Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:124-130 [Conf]
  18. Jean-Pascal Pfister, Wulfram Gerstner
    Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  19. Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
    Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  20. J. Leo van Hemmen, Wulfram Gerstner, Andreas V. M. Herz, Reimer Kühn, B. Sulzer, M. Vaas
    Encoding and Decoding of Patterns which are Correlated in Space and Time. [Citation Graph (0, 0)][DBLP]
    ÖGAI, 1990, pp:153-162 [Conf]
  21. Fabrizio Smeraldi, Josef Bigün, Wulfram Gerstner
    Support Vector Features and the Role of Dimensionality in Face Authentication. [Citation Graph (0, 0)][DBLP]
    SVM, 2002, pp:249-259 [Conf]
  22. José del R. Millán, Frédéric Renkens, Josep Mouriño, Wulfram Gerstner
    Brain-actuated interaction. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2004, v:159, n:1-2, pp:241-259 [Journal]
  23. Wulfram Gerstner, Werner M. Kistler
    Mathematical formulations of Hebbian learning. [Citation Graph (0, 0)][DBLP]
    Biological Cybernetics, 2002, v:87, n:5-6, pp:404-415 [Journal]
  24. Ricardo Chavarriaga, Thomas Strösslin, Denis Sheynikhovich, Wulfram Gerstner
    Competition between cue response and place response: a model of rat navigation behaviour. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2005, v:17, n:1-2, pp:167-183 [Journal]
  25. Angelo Arleo, Wulfram Gerstner
    Spatial orientation in navigating agents: Modeling head-direction cells. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:1059-1065 [Journal]
  26. Alix Herrmann, Wulfram Gerstner
    Effect of noise on neuron transient response. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:147-154 [Journal]
  27. Ofer Melamed, Gilad Silberberg, Henry Markram, Wulfram Gerstner, Magnus J. E. Richardson
    Subthreshold cross-correlations between cortical neurons: A reference model with static synapses. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:65, n:, pp:685-690 [Journal]
  28. Hans E. Plesser, Wulfram Gerstner
    Escape rate models for noisy integrate-and-free neurons. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:219-224 [Journal]
  29. Mona Spiridon, Carson C. Chow, Wulfram Gerstner
    Effect of correlations on signal transmission in a population of spiking neurons. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2000, v:32, n:, pp:529-535 [Journal]
  30. Mona Spiridon, Wulfram Gerstner
    The accuracy of the population vector estimate in networks of integrate-and-fire type neurons using stationary and transient stimuli. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:38, n:, pp:927-934 [Journal]
  31. Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strösslin, Wulfram Gerstner
    Adaptive sensory processing for efficient place coding. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:10-12, pp:1211-1214 [Journal]
  32. Laurent Badel, Wulfram Gerstner, Magnus J. E. Richardson
    Dependence of the spike-triggered average voltage on membrane response properties. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:10-12, pp:1062-1065 [Journal]
  33. Alix Herrmann, Wulfram Gerstner
    Noise and the PSTH Response to Current Transients: I. General Theory and Application to the Integrate-and-Fire Neuron. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Neuroscience, 2001, v:11, n:2, pp:135-151 [Journal]
  34. Alix Herrmann, Wulfram Gerstner
    Noise and the PSTH Response to Current Transients: II. Integrate-and-Fire Model with Slow Recovery and Application to Motoneuron Data. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Neuroscience, 2002, v:12, n:2, pp:83-95 [Journal]
  35. Wulfram Gerstner, L. F. Abbott
    Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Neuroscience, 1997, v:4, n:1, pp:79-94 [Journal]
  36. C. Fohlmeister, Wulfram Gerstner, Raphael Ritz, J. Leo van Hemmen
    Spontaneous excitations in the visual cortex: stripes, spirals, rings, and collective bursts. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1995, v:7, n:5, pp:905-914 [Journal]
  37. Wulfram Gerstner
    Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:1, pp:43-89 [Journal]
  38. Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen
    Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:12, pp:2709-2741 [Journal]
  39. Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen, Hermann Wagner
    Extracting Oscillations: Neuronal Coincidence Detection with Noisy Periodic Spike Input. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:8, pp:1987-2017 [Journal]
  40. Werner M. Kistler, Wulfram Gerstner
    Stable Propagation of Activity Pulses in Populations of Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:5, pp:987-997 [Journal]
  41. Werner M. Kistler, Wulfram Gerstner, J. Leo van Hemmen
    Reduction of the Hogkin-Huxley Equations to a Single-Variable Threshold Model. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:5, pp:1015-1045 [Journal]
  42. Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner
    Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:6, pp:1318-1348 [Journal]
  43. Hans E. Plesser, Wulfram Gerstner
    Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:2, pp:367-384 [Journal]
  44. Magnus J. E. Richardson, Wulfram Gerstner
    Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:4, pp:923-947 [Journal]
  45. Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
    Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2007, v:19, n:3, pp:639-671 [Journal]
  46. Wulfram Gerstner
    Coding properties of spiking neurons: reverse and cross-correlations. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:6-7, pp:599-610 [Journal]
  47. Thomas Strösslin, Denis Sheynikhovich, Ricardo Chavarriaga, Wulfram Gerstner
    Robust self-localisation and navigation based on hippocampal place cells. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2005, v:18, n:9, pp:1125-1140 [Journal]
  48. Gediminas Luksys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner
    Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:937-944 [Conf]
  49. Claudia Clopath, Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner
    Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2007, v:70, n:10-12, pp:1668-1673 [Journal]

  50. A Bayesian kernel for the prediction of neuron properties from binary gene profiles. [Citation Graph (, )][DBLP]


  51. An online Hebbian learning rule that performs Independent Component Analysis. [Citation Graph (, )][DBLP]


  52. Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning. [Citation Graph (, )][DBLP]


  53. Phenomenological models of synaptic plasticity based on spike timing. [Citation Graph (, )][DBLP]


  54. Special issue on quantitative neuron modeling. [Citation Graph (, )][DBLP]


  55. Extracting non-linear integrate-and-fire models from experimental data using dynamic I - V curves. [Citation Graph (, )][DBLP]


  56. The quantitative single-neuron modeling competition. [Citation Graph (, )][DBLP]


  57. Firing patterns in the adaptive exponential integrate-and-fire model. [Citation Graph (, )][DBLP]


  58. Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. [Citation Graph (, )][DBLP]


  59. Emergence of spatiotemporal receptive fields and its application to motion detection. [Citation Graph (, )][DBLP]


  60. A biologically motivated and analytically soluble model of collective oscillations in the cortex. [Citation Graph (, )][DBLP]


  61. Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns. [Citation Graph (, )][DBLP]


  62. A biologically motivated and analytically soluble model of collective oscillations in the cortex. [Citation Graph (, )][DBLP]


  63. Universality in neural networks: the importance of the 'mean firing rate'. [Citation Graph (, )][DBLP]


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