Marco Congedo
Cognitive Neuroscience · 2007–2018
A researcher in the Science corpus: 7 papers; trusts 33 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 92 citations into it; #1,234 of 10,852 by trust here, #1,769 by citations
- Signal Processing — 28 citations into it
- Artificial Intelligence — 27 citations into it
- Cellular and Molecular Neuroscience — 26 citations into it; #807 of 2,998 by trust here, #1,858 by citations
- Computer Vision and Pattern Recognition — 24 citations into it
- Electrical and Electronic Engineering — 17 citations into it; #6,404 of 16,539 by trust here, #5,738 by citations
- Computational Theory and Mathematics — 14 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
Whom Marco Congedo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Benjamin Blankertz
- Xavier Pennec
- Maher Moakher
- Alexandre Barachant
- Jonathan R. Wolpaw
- Fabien Lotte
- Pierre Fillard
- Christopher K. I. Williams
- Geoffrey E. Hinton
- Herbert Ramoser
Who trusts Marco Congedo overall
- Fabien Lotte
- Jae-Hwan Kang
- Paolo Zanini
- He He
- M. Rashid
- Jang-Han Bae
- Vernon J. Lawhern
- Ce Ju
- Florian Yger
- Dongrui Wu
Papers from Marco Congedo's perspective
Ordered by how strongly the researchers Marco Congedo trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Neural Networks for Pattern Recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A review of classification algorithms for EEG-based brain–computer interfaces (2007) — 2,742 citations
- Classification of covariance matrices using a Riemannian-based kernel for BCI applications (2013) — 493 citations
- A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update (2018) — 2,013 citations
- Transfer Learning: A Riemannian Geometry Framework With Applications to Brain–Computer Interfaces (2018) — 347 citations
- Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review (2017) — 418 citations
- Multiclass Brain–Computer Interface Classification by Riemannian Geometry (2012) — 838 citations
- The neural correlates of tinnitus-related distress (2010) — 395 citations