Matthias Krauledat
Cognitive Neuroscience · 2006–2008
A researcher in the Science corpus: 7 papers; trusts 42 researchers and is trusted by 52 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 71 citations into it; #1,146 of 10,852 by trust here, #1,607 by citations
- Cellular and Molecular Neuroscience — 33 citations into it; #690 of 2,998 by trust here, #986 by citations
- Artificial Intelligence — 26 citations into it; #5,660 of 35,345 by trust here, #8,619 by citations
- Electrical and Electronic Engineering — 21 citations into it; #4,534 of 16,539 by trust here, #8,322 by citations
- Signal Processing — 14 citations into it; #4,372 of 7,572 by trust here, #3,673 by citations
- Statistical Learning Theory — 13 citations into it
- Statistics and Probability — 11 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
Whom Matthias Krauledat trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Benjamin Blankertz
- K. Müller
- Guido Dornhege
- Masashi Sugiyama
- Herbert Ramoser
- Yi Lin
- Jonathan R. Wolpaw
- Gert Pfurtscheller
- Bernhard Schölkopf
- Robert E. Schapire
Who trusts Matthias Krauledat overall
- Benjamin Blankertz
- Masashi Sugiyama
- Carmen Vidaurre
- Fabien Lotte
- K. Müller
- Hirotaka Hachiya
- Steven Lemm
- Zhangjie Cao
- Mingsheng Long
- Kai Keng Ang
Papers from Matthias Krauledat's perspective
Ordered by how strongly the researchers Matthias Krauledat 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
Their papers
- Covariate Shift Adaptation by Importance Weighted Cross Validation (2007) — 1,089 citations
- The Berlin Brain-Computer Interface: Accurate performance from first-session in BCI-naive subjects (2008) — 339 citations
- Combined Optimization of Spatial and Temporal Filters for Improving Brain-Computer Interfacing (2006) — 406 citations
- Machine learning for real-time single-trial EEG-analysis: from brain-computer interfacing to mental state monitoring. (2008) — 506 citations
- The non-invasive Berlin Brain-Computer Interface: Fast acquisition of effective performance in untrained subjects (2007) — 1,006 citations
- Towards adaptive classification for BCI (2006) — 484 citations
- The Berlin brain-computer interface: EEG-based communication without subject training (2006) — 358 citations