Mikael Kågebäck
Natural Language Processing · 2015–2016
A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 16 citations into it
- Artificial Intelligence — 14 citations into it; #15,297 of 35,345 by trust here, #20,377 by citations
- Reinforcement Learning — 8 citations into it; #1,174 of 2,242 by trust here, #1,705 by citations
- Representation & Self-Supervised Learning — 8 citations into it
Whom Mikael Kågebäck trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Tomas Mikolov
- Geoffrey E. Hinton
- L. V. D. van der Maaten
- Robert Tibshirani
- Hinrich Schütze
- Richard S. Sutton
- Alex Krizhevsky
- Sergey Ioffe
- Yann LeCun
Who trusts Mikael Kågebäck overall
Papers from Mikael Kågebäck's perspective
Ordered by how strongly the researchers Mikael Kågebäck 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence (2016) — 70 citations
- Neural context embeddings for automatic discovery of word senses (2015) — 26 citations