Fabien Lotte
Cognitive Neuroscience · 2007–2018
A researcher in the Science corpus: 8 papers; trusts 77 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 110 citations into it; #1,061 of 10,852 by trust here, #1,539 by citations
- Cellular and Molecular Neuroscience — 45 citations into it; #437 of 2,998 by trust here, #1,454 by citations
- Electrical and Electronic Engineering — 32 citations into it; #2,742 of 16,539 by trust here, #5,149 by citations
- Signal Processing — 31 citations into it; #3,973 of 7,572 by trust here, #4,373 by citations
- Artificial Intelligence — 29 citations into it
- Human-Computer Interaction — 18 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Computational Theory and Mathematics — 11 citations into it
Whom Fabien Lotte trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Benjamin Blankertz
- Gert Pfurtscheller
- Olivier Ledoit
- K. Müller
- Jonathan R. Wolpaw
- Carmen Vidaurre
- Guido Dornhege
- Thorsten Oliver Zander
- Christa Neuper
- Herbert Ramoser
Who trusts Fabien Lotte overall
- Dongrui Wu
- Florian Yger
- O-Yeon Kwon
- Vernon J. Lawhern
- Christian Andreas Kothe
- Dennis J. McFarland
- Cuntai Guan
- Luis F. Nicolás-Alonso
- Maxime Bérar
- Hubert Cecotti
Papers from Fabien Lotte's perspective
Ordered by how strongly the researchers Fabien Lotte 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Neural Networks for Pattern Recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A review of classification algorithms for EEG-based brain–computer interfaces (2007) — 2,742 citations
- Brain-Computer Interfaces, Virtual Reality, and Videogames (2008) — 390 citations
- Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design (2013) — 301 citations
- Signal Processing Approaches to Minimize or Suppress Calibration Time in Oscillatory Activity-Based Brain–Computer Interfaces (2015) — 303 citations
- A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update (2018) — 2,013 citations
- Riemannian Approaches in Brain-Computer Interfaces: A Review (2017) — 390 citations
- Brain-Computer Interfaces: Beyond Medical Applications (2012) — 376 citations
- Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms (2011) — 1,030 citations