default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDWulfram Gerstner
Person information
- affiliation: Swiss Federal Institute of Technology in Lausanne, Switzerland
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j85]Ana Stanojevic, Stanislaw Wozniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi
, Wulfram Gerstner:
Corrigendum to 'An exact mapping from ReLU networks to spiking neural networks' [Neural Networks Volume 168 (2023) Pages 74-88]. Neural Networks 169: 622 (2024)- [j84]Martin L. L. R. Barry, Wulfram Gerstner:
Fast adaptation to rule switching using neuronal surprise. PLoS Comput. Biol. 20(2) (2024) - [j83]Carlos S. N. Brito, Wulfram Gerstner:
Learning what matters: Synaptic plasticity with invariance to second-order input correlations. PLoS Comput. Biol. 20(2) (2024) - [c44]Flavio Martinelli, Berfin Simsek, Wulfram Gerstner, Johanni Brea:
Expand-and-Cluster: Parameter Recovery of Neural Networks. ICML 2024 - 2023
- [j82]Ana Stanojevic, Stanislaw Wozniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner:
An exact mapping from ReLU networks to spiking neural networks. Neural Networks 168: 74-88 (2023) - [j81]Marta Boscaglia, Chiara Gastaldi, Wulfram Gerstner, Rodrigo Quian Quiroga:
A dynamic attractor network model of memory formation, reinforcement and forgetting. PLoS Comput. Biol. 19(12) (2023) - [c43]Zeng Ren, Wulfram Gerstner, Martin Rohrmeier:
Music as Flow: A Formal Representation of Hierarchical Processes in Music. ISMIR 2023: 627-633 - [c42]Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea:
Should Under-parameterized Student Networks Copy or Average Teacher Weights? NeurIPS 2023 - [c41]Christos Sourmpis, Carl C. H. Petersen, Wulfram Gerstner, Guillaume Bellec:
Trial matching: capturing variability with data-constrained spiking neural networks. NeurIPS 2023 - [i25]Johanni Brea, Flavio Martinelli, Berfin Simsek, Wulfram Gerstner:
MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately). CoRR abs/2301.10638 (2023) - [i24]Flavio Martinelli, Berfin Simsek, Johanni Brea, Wulfram Gerstner:
Expand-and-Cluster: Exact Parameter Recovery of Neural Networks. CoRR abs/2304.12794 (2023) - [i23]Martin Barry, Guillaume Bellec, Wulfram Gerstner:
GateON: an unsupervised method for large scale continual learning. CoRR abs/2306.01690 (2023) - [i22]Ana Stanojevic, Stanislaw Wozniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner:
Are training trajectories of deep single-spike and deep ReLU network equivalent? CoRR abs/2306.08744 (2023) - [i21]Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea:
Should Under-parameterized Student Networks Copy or Average Teacher Weights? CoRR abs/2311.01644 (2023) - 2022
- [j80]Vasiliki Liakoni, Marco P. Lehmann, Alireza Modirshanechi, Johanni Brea, Antoine Lutti, Wulfram Gerstner, Kerstin Preuschoff:
Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making. NeuroImage 246: 118780 (2022) - [c40]Ana Stanojevic, Evangelos Eleftheriou, Giovanni Cherubini, Stanislaw Wozniak, Angeliki Pantazi, Wulfram Gerstner:
Approximating Relu Networks by Single-Spike Computation. ICIP 2022: 1901-1905 - [c39]Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner:
Kernel Memory Networks: A Unifying Framework for Memory Modeling. NeurIPS 2022 - [c38]Shuqi Wang, Valentin Schmutz, Guillaume Bellec, Wulfram Gerstner:
Mesoscopic modeling of hidden spiking neurons. NeurIPS 2022 - [i20]Shuqi Wang, Valentin Schmutz, Guillaume Bellec, Wulfram Gerstner:
Mesoscopic modeling of hidden spiking neurons. CoRR abs/2205.13493 (2022) - [i19]Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner:
Kernel Memory Networks: A Unifying Framework for Memory Modeling. CoRR abs/2208.09416 (2022) - [i18]Ana Stanojevic, Stanislaw Wozniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner:
An Exact Mapping From ReLU Networks to Spiking Neural Networks. CoRR abs/2212.12522 (2022) - 2021
- [j79]Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea:
Learning in Volatile Environments With the Bayes Factor Surprise. Neural Comput. 33(2): 269-340 (2021) - [j78]He A. Xu, Alireza Modirshanechi, Marco P. Lehmann, Wulfram Gerstner, Michael H. Herzog:
Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making. PLoS Comput. Biol. 17(6) (2021) - [j77]Chiara Gastaldi, Tilo Schwalger, Emanuela De Falco, Rodrigo Quian Quiroga, Wulfram Gerstner:
When shared concept cells support associations: Theory of overlapping memory engrams. PLoS Comput. Biol. 17(12) (2021) - [c37]Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea:
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. ICML 2021: 9722-9732 - [c36]Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner:
Fitting summary statistics of neural data with a differentiable spiking network simulator. NeurIPS 2021: 18552-18563 - [c35]Bernd Illing, Jean Ventura, Guillaume Bellec, Wulfram Gerstner:
Local plasticity rules can learn deep representations using self-supervised contrastive predictions. NeurIPS 2021: 30365-30379 - [i17]Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea:
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. CoRR abs/2105.12221 (2021) - [i16]Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner:
Fitting summary statistics of neural data with a differentiable spiking network simulator. CoRR abs/2106.10064 (2021) - 2020
- [j76]Simone Carlo Surace, Jean-Pascal Pfister, Wulfram Gerstner, Johanni Brea:
On the choice of metric in gradient-based theories of brain function. PLoS Comput. Biol. 16(4) (2020) - [i15]Bernd Illing, Wulfram Gerstner, Guillaume Bellec:
Towards truly local gradients with CLAPP: Contrastive, Local And Predictive Plasticity. CoRR abs/2010.08262 (2020)
2010 – 2019
- 2019
- [j75]Chiara Gastaldi, Samuel P. Muscinelli, Wulfram Gerstner:
Optimal Stimulation Protocol in a Bistable Synaptic Consolidation Model. Frontiers Comput. Neurosci. 13: 78 (2019) - [j74]Bernd Illing, Wulfram Gerstner, Johanni Brea:
Biologically plausible deep learning - But how far can we go with shallow networks? Neural Networks 118: 90-101 (2019) - [j73]Alexander Seeholzer, Moritz Deger, Wulfram Gerstner:
Stability of working memory in continuous attractor networks under the control of short-term plasticity. PLoS Comput. Biol. 15(4) (2019) - [j72]Samuel P. Muscinelli, Wulfram Gerstner, Tilo Schwalger:
How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. PLoS Comput. Biol. 15(6) (2019) - [i14]Bernd Illing, Wulfram Gerstner, Johanni Brea:
Biologically plausible deep learning - but how far can we go with shallow networks? CoRR abs/1905.04101 (2019) - [i13]Johanni Brea, Berfin Simsek, Bernd Illing, Wulfram Gerstner:
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape. CoRR abs/1907.02911 (2019) - [i12]Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea:
An Approximate Bayesian Approach to Surprise-Based Learning. CoRR abs/1907.02936 (2019) - [i11]Roman Pogodin, Dane S. Corneil, Alexander Seeholzer, Joseph Heng, Wulfram Gerstner:
Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks. CoRR abs/1910.10559 (2019) - 2018
- [j71]Marco Martinolli, Wulfram Gerstner, Aditya Gilra:
Multi-Timescale Memory Dynamics Extend Task Repertoire in a Reinforcement Learning Network With Attention-Gated Memory. Frontiers Comput. Neurosci. 12: 50 (2018) - [j70]Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner:
Balancing New against Old Information: The Role of Puzzlement Surprise in Learning. Neural Comput. 30(1) (2018) - [j69]Hesam Setareh, Moritz Deger, Wulfram Gerstner:
Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagation. PLoS Comput. Biol. 14(7) (2018) - [c34]Dane S. Corneil, Wulfram Gerstner, Johanni Brea:
Efficient ModelBased Deep Reinforcement Learning with Variational State Tabulation. ICML 2018: 1057-1066 - [c33]Aditya Gilra, Wulfram Gerstner:
Non-Linear Motor Control by Local Learning in Spiking Neural Networks. ICML 2018: 1768-1777 - [i10]Dane S. Corneil, Wulfram Gerstner, Johanni Brea:
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation. CoRR abs/1802.04325 (2018) - [i9]Florian Colombo, Wulfram Gerstner:
BachProp: Learning to Compose Music in Multiple Styles. CoRR abs/1802.05162 (2018) - [i8]Florian Colombo, Johanni Brea, Wulfram Gerstner:
Learning to Generate Music with BachProp. CoRR abs/1812.06669 (2018) - 2017
- [j68]Hesam Setareh, Moritz Deger, Carl C. H. Petersen, Wulfram Gerstner:
Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons. Frontiers Comput. Neurosci. 11: 52 (2017) - [j67]Samuel P. Muscinelli, Wulfram Gerstner, Johanni Brea:
Exponentially Long Orbits in Hopfield Neural Networks. Neural Comput. 29(2): 458-484 (2017) - [j66]Tilo Schwalger, Moritz Deger, Wulfram Gerstner:
Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size. PLoS Comput. Biol. 13(4) (2017) - [c32]Florian Colombo, Alexander Seeholzer, Wulfram Gerstner:
Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation. EvoMUSART 2017: 81-96 - [r2]Wulfram Gerstner:
Biological Learning: Synaptic Plasticity, Hebb Rule and Spike Timing Dependent Plasticity. Encyclopedia of Machine Learning and Data Mining 2017: 140-143 - [i7]Aditya Gilra, Wulfram Gerstner:
Predicting non-linear dynamics: a stable local learning scheme for recurrent spiking neural networks. CoRR abs/1702.06463 (2017) - [i6]Marco Martinolli, Wulfram Gerstner, Aditya Gilra:
Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory. CoRR abs/1712.10062 (2017) - [i5]Aditya Gilra, Wulfram Gerstner:
Non-linear motor control by local learning in spiking neural networks. CoRR abs/1712.10158 (2017) - 2016
- [j65]Skander Mensi, Olivier Hagens, Wulfram Gerstner, Christian Pozzorini:
Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons. PLoS Comput. Biol. 12(2) (2016) - [j64]Carlos S. N. Brito, Wulfram Gerstner:
Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation. PLoS Comput. Biol. 12(9) (2016) - [i4]Carlos S. N. Brito, Wulfram Gerstner:
Nonlinear Hebbian learning as a unifying principle in receptive field formation. CoRR abs/1601.00701 (2016) - [i3]Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner:
Balancing New Against Old Information: The Role of Surprise. CoRR abs/1606.05642 (2016) - [i2]Florian Colombo, Samuel P. Muscinelli, Alexander Seeholzer, Johanni Brea, Wulfram Gerstner:
Algorithmic Composition of Melodies with Deep Recurrent Neural Networks. CoRR abs/1606.07251 (2016) - [i1]Thomas Mesnard, Wulfram Gerstner, Johanni Brea:
Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity. CoRR abs/1612.03214 (2016) - 2015
- [j63]Christian Pozzorini, Skander Mensi, Olivier Hagens, Richard Naud, Christof Koch, Wulfram Gerstner:
Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models. PLoS Comput. Biol. 11(6) (2015) - [c31]Dane S. Corneil, Wulfram Gerstner:
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like Environments. NIPS 2015: 1684-1692 - 2014
- [j62]Danilo Jimenez Rezende, Wulfram Gerstner:
Stochastic variational learning in recurrent spiking networks. Frontiers Comput. Neurosci. 8: 38 (2014) - [j61]Richard Naud, Brice Bathellier, Wulfram Gerstner:
Spike-timing prediction in cortical neurons with active dendrites. Frontiers Comput. Neurosci. 8: 90 (2014) - [j60]Friedemann Zenke, Wulfram Gerstner:
Limits to high-speed simulations of spiking neural networks using general-purpose computers. Frontiers Neuroinformatics 8: 76 (2014) - 2013
- [j59]Nicolas Frémaux, Henning Sprekeler, Wulfram Gerstner:
Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons. PLoS Comput. Biol. 9(4) (2013) - [j58]Friedemann Zenke, Guillaume Hennequin, Wulfram Gerstner:
Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector. PLoS Comput. Biol. 9(11) (2013) - 2012
- [j57]Johannes Rüter, Nicolas Marcille, Henning Sprekeler, Wulfram Gerstner, Michael H. Herzog:
Paradoxical Evidence Integration in Rapid Decision Processes. PLoS Comput. Biol. 8(2) (2012) - [j56]Richard Naud, Wulfram Gerstner:
Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram. PLoS Comput. Biol. 8(10) (2012) - 2011
- [j55]Felipe Gerhard, Gordon Pipa, Bruss Lima, Sergio Neuenschwander, Wulfram Gerstner:
Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect? Frontiers Comput. Neurosci. 5: 4 (2011) - [j54]Richard Naud, Felipe Gerhard, Skander Mensi, Wulfram Gerstner:
Improved Similarity Measures for Small Sets of Spike Trains. Neural Comput. 23(12): 3016-3069 (2011) - [c30]Amir Hesam Salavati, K. Raj Kumar, Mohammad Amin Shokrollahi, Wulfram Gerstner:
Neural pre-coding increases the pattern retrieval capacity of Hopfield and Bidirectional Associative Memories. ISIT 2011: 850-854 - [c29]Danilo Jimenez Rezende, Daan Wierstra, Wulfram Gerstner:
Variational Learning for Recurrent Spiking Networks. NIPS 2011: 136-144 - [c28]Skander Mensi, Richard Naud, Wulfram Gerstner:
From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models. NIPS 2011: 1377-1385 - 2010
- [j53]Guillaume Hennequin, Wulfram Gerstner, Jean-Pascal Pfister:
STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission. Frontiers Comput. Neurosci. 4: 143 (2010) - [j52]Jesper Sjöström, Wulfram Gerstner:
Spike-timing dependent plasticity. Scholarpedia 5(2): 1362 (2010) - [c27]Felipe Gerhard, Wulfram Gerstner:
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models. NIPS 2010: 703-711 - [r1]Wulfram Gerstner:
Biological Learning: Synaptic Plasticity, Hebb Rule and Spike TimingDependent Plasticity. Encyclopedia of Machine Learning 2010: 111-132
2000 – 2009
- 2009
- [j51]Eleni Vasilaki, Nicolas Frémaux, Robert Urbanczik, Walter Senn, Wulfram Gerstner:
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail. PLoS Comput. Biol. 5(12) (2009) - [j50]Wulfram Gerstner, Romain Brette:
Adaptive exponential integrate-and-fire model. Scholarpedia 4(6): 8427 (2009) - [c26]Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner:
Code-specific policy gradient rules for spiking neurons. NIPS 2009: 1741-1749 - 2008
- [j49]Abigail Morrison, Markus Diesmann, Wulfram Gerstner:
Phenomenological models of synaptic plasticity based on spike timing. Biol. Cybern. 98(6): 459-478 (2008) - [j48]Renaud Jolivet, Arnd Roth, Felix Schürmann, Wulfram Gerstner, Walter Senn:
Special issue on quantitative neuron modeling. Biol. Cybern. 99(4-5): 237-239 (2008) - [j47]Richard Naud, Nicolas Marcille, Claudia Clopath, Wulfram Gerstner:
Firing patterns in the adaptive exponential integrate-and-fire model. Biol. Cybern. 99(4-5): 335-347 (2008) - [j46]Laurent Badel, Sandrine Lefort, Thomas K. Berger, Carl C. H. Petersen, Wulfram Gerstner, Magnus J. E. Richardson:
Extracting non-linear integrate-and-fire models from experimental data using dynamic I - V curves. Biol. Cybern. 99(4-5): 361-370 (2008) - [j45]Renaud Jolivet, Felix Schürmann, Thomas K. Berger, Richard Naud, Wulfram Gerstner, Arnd Roth:
The quantitative single-neuron modeling competition. Biol. Cybern. 99(4-5): 417-426 (2008) - [j44]Brice Bathellier, Alan Carleton, Wulfram Gerstner:
Gamma Oscillations in a Nonlinear Regime: A Minimal Model Approach Using Heterogeneous Integrate-and-Fire Networks. Neural Comput. 20(12): 2973-3002 (2008) - [j43]Claudia Clopath, Lorric Ziegler, Eleni Vasilaki, Lars Büsing, Wulfram Gerstner:
Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression. PLoS Comput. Biol. 4(12) (2008) - [j42]Wulfram Gerstner:
Spike-response model. Scholarpedia 3(12): 1343 (2008) - [c25]Gediminas Luksys, Carmen Sandi, Wulfram Gerstner:
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning. NIPS 2008: 1001-1008 - 2007
- [j41]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. Neurocomputing 70(10-12): 1668-1673 (2007) - [j40]Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner:
Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution. Neural Comput. 19(3): 639-671 (2007) - [j39]Michael H. Herzog, Michael Esfeld, Wulfram Gerstner:
Consciousness & the small network argument. Neural Networks 20(9): 1054-1056 (2007) - [c24]Claudia Clopath, André Longtin, Wulfram Gerstner:
An online Hebbian learning rule that performs Independent Component Analysis. NIPS 2007: 321-328 - 2006
- [j38]Laurent Badel, Wulfram Gerstner, Magnus J. E. Richardson:
Dependence of the spike-triggered average voltage on membrane response properties. Neurocomputing 69(10-12): 1062-1065 (2006) - [j37]Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strösslin, Wulfram Gerstner:
Adaptive sensory processing for efficient place coding. Neurocomputing 69(10-12): 1211-1214 (2006) - [j36]Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner:
Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J. Comput. Neurosci. 21(1): 35-49 (2006) - [j35]Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner:
Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. Neural Comput. 18(6): 1318-1348 (2006) - [c23]Gediminas Luksys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner:
Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning. NIPS 2006: 937-944 - 2005
- [j34]Ricardo Chavarriaga, Thomas Strösslin, Denis Sheynikhovich, Wulfram Gerstner:
Competition between cue response and place response: a model of rat navigation behaviour. Connect. Sci. 17(1-2): 167-183 (2005) - [j33]Ofer Melamed, Gilad Silberberg, Henry Markram, Wulfram Gerstner, Magnus J. E. Richardson:
Subthreshold cross-correlations between cortical neurons: A reference model with static synapses. Neurocomputing 65-66: 685-690 (2005) - [j32]Magnus J. E. Richardson, Ofer Melamed, Gilad Silberberg, Wulfram Gerstner, Henry Markram:
Short-Term Synaptic Plasticity Orchestrates the Response of Pyramidal Cells and Interneurons to Population Bursts. J. Comput. Neurosci. 18(3): 323-331 (2005) - [j31]Magnus J. E. Richardson, Wulfram Gerstner:
Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance. Neural Comput. 17(4): 923-947 (2005) - [j30]Ricardo Chavarriaga, Thomas Strösslin, Denis Sheynikhovich, Wulfram Gerstner:
A computational model of parallel navigation systems in rodents. Neuroinformatics 3(3): 223-241 (2005) - [j29]Thomas Strösslin, Denis Sheynikhovich, Ricardo Chavarriaga, Wulfram Gerstner:
Robust self-localisation and navigation based on hippocampal place cells. Neural Networks 18(9): 1125-1140 (2005) - [c22]Thomas Strösslin, Ricardo Chavarriaga, Denis Sheynikhovich, Wulfram Gerstner:
Modelling Path Integrator Recalibration Using Hippocampal Place Cells. ICANN (1) 2005: 51-56 - [c21]François Fleuret, Wulfram Gerstner:
A Bayesian kernel for the prediction of neuron properties from binary gene profiles. ICMLA 2005 - [c20]Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strösslin, Wulfram Gerstner:
Spatial Representation and Navigation in a Bio-inspired Robot. Biomimetic Neural Learning for Intelligent Robots 2005: 245-264 - [c19]Renaud Jolivet, Alexander Rauch, Hans-Rudolf Lüscher, Wulfram Gerstner:
Integrate-and-Fire models with adaptation are good enough. NIPS 2005: 595-602 - [c18]Jean-Pascal Pfister, Wulfram Gerstner:
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects. NIPS 2005: 1081-1088 - 2004
- [j28]José del R. Millán, Frédéric Renkens, Josep Mouriño, Wulfram Gerstner:
Brain-actuated interaction. Artif. Intell. 159(1-2): 241-259 (2004) - [j27]José del R. Millán, Frédéric Renkens, Josep Mouriño, Wulfram Gerstner:
Noninvasive brain-actuated control of a mobile robot by human EEG. IEEE Trans. Biomed. Eng. 51(6): 1026-1033 (2004) - [j26]Angelo Arleo, Fabrizio Smeraldi, Wulfram Gerstner:
Cognitive navigation based on nonuniform Gabor space sampling, unsupervised growing networks, and reinforcement learning. IEEE Trans. Neural Networks 15(3): 639-652 (2004) - [c17]Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner:
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model. NIPS 2004: 1409-1416 - 2003
- [c16]Jean-Pascal Pfister, David Barber, Wulfram Gerstner:
Optimal Hebbian Learning: A Probabilistic Point of View. ICANN 2003: 92-98 - [c15]Julien Mayor, Wulfram Gerstner:
Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network. ICANN 2003: 839-845 - [c14]