Henning Sprekeler
Cognitive Neuroscience · 2007–2016
A researcher in the Science corpus: 9 papers; trusts 41 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 120 citations into it; #959 of 10,852 by trust here, #2,336 by citations
- Cellular and Molecular Neuroscience — 96 citations into it; #225 of 2,998 by trust here, #838 by citations
- Electrical and Electronic Engineering — 48 citations into it; #3,154 of 16,539 by trust here, #8,802 by citations
- Neuroscience — 23 citations into it
- Representation & Self-Supervised Learning — 7 citations into it
- Signal Processing — 7 citations into it; #2,788 of 7,572 by trust here, #5,829 by citations
- Analytical Chemistry — 5 citations into it; #304 of 1,254 by trust here, #626 by citations
- Artificial Intelligence — 5 citations into it
Whom Henning Sprekeler trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Laurenz Wiskott
- Aapo Hyvärinen
- Pietro Berkes
- Terrence J. Sejnowski
- Anthony J. Bell
- Sen Song
- Wulfram Gerstner
- Mathias Franzius
- Eugene M. Izhikevich
- Guoqiang Bi
Who trusts Henning Sprekeler overall
- Aapo Hyvärinen
- Nitish Srivastava
- Friedemann Zenke
- Wulfram Gerstner
- Hermanni Hälvä
- Hiroshi Morioka
- Laurenz Wiskott
- J. Urgen Schmidhuber
- Varun Raj Kompella
- Wolfram Schultz
Papers from Henning Sprekeler's perspective
Ordered by how strongly the researchers Henning Sprekeler trusts endorse each paper. Same corpus, a different order for every researcher.
- Reinforcement Learning: An Introduction
- An Information-Maximization Approach to Blind Separation and Blind Deconvolution
- Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type
- Gradient-based learning applied to document recognition
- Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs
- Slow Feature Analysis: Unsupervised Learning of Invariances
- Separation of a mixture of independent signals using time delayed correlations.
- Nonlinear independent component analysis: Existence and uniqueness results
- Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
- Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
Their papers
- An extension of slow feature analysis for nonlinear blind source separation (2014) — 76 citations
- Functional Requirements for Reward-Modulated Spike-Timing-Dependent Plasticity (2010) — 154 citations
- Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons (2016) — 50 citations
- Inhibitory synaptic plasticity: spike timing-dependence and putative network function (2013) — 128 citations
- Receptive field formation by interacting excitatory and inhibitory synaptic plasticity (2016) — 37 citations
- Slow Feature Analysis (2014) — 54 citations
- Perceptual learning, roving and the unsupervised bias. (2012) — 33 citations
- Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks (2011) — 766 citations
- Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells (2007) — 242 citations