Jean-Pascal Pfister

Cognitive Neuroscience · 2006–2021

A researcher in the Science corpus: 8 papers; trusts 46 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 46 citations into it; #772 of 10,852 by trust here, #2,529 by citations
• Cellular and Molecular Neuroscience — 41 citations into it; #188 of 2,998 by trust here, #970 by citations
• Artificial Intelligence — 34 citations into it; #19,783 of 35,345 by trust here, #25,809 by citations
• Electrical and Electronic Engineering — 29 citations into it; #680 of 16,539 by trust here, #4,925 by citations
• Probabilistic & Bayesian Methods — 29 citations into it
• Neuroscience — 19 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 9 citations into it

Whom Jean-Pascal Pfister trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Guoqiang Bi
2. Geoffrey E. Hinton
3. Wulfram Gerstner
4. Mu-Ming Poo
5. Robert Froemke
6. Per Jesper Sjöström
7. Gianluigi Mongillo
8. John E. Lisman
9. John J. Hopfield
10. Ilya Sutskever

Who trusts Jean-Pascal Pfister overall

1. Friedemann Zenke
2. Pierre Yger
3. Claudia Clopath
4. Wulfram Gerstner
5. Matthieu Gilson
6. Lorric Ziegler
7. A. Watt
8. Baktash Babadi
9. Julijana Gjorgjieva
10. Robert Froemke

Papers from Jean-Pascal Pfister's perspective

Ordered by how strongly the researchers Jean-Pascal Pfister trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. GENERATIVE ADVERSARIAL NETS
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Matching Recall and Storage in Sequence Learning with Spiking Neural Networks (2013) — 118 citations
• Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity (2006) — 669 citations
• A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations (2011) — 208 citations
• Synaptic plasticity as Bayesian inference (2021) — 48 citations
• Approximating the Predictive Distribution via Adversarially-Trained Hypernetworks (2018)
• Sequence learning with hidden units in spiking neural networks (2011) — 45 citations
• Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials (2010)
• Know Thy Neighbour: A Normative Theory of Synaptic Depression (2009) — 16 citations