B. Meyer

Artificial Intelligence · with Gross · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 94 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #17,644 of 35,345 by trust here, #25,809 by citations
• Computer Vision and Pattern Recognition — 31 citations into it; #11,097 of 21,575 by trust here, #17,757 by citations
• Model Architectures — 21 citations into it
• Efficiency & Compression — 20 citations into it
• Natural Language Processing — 14 citations into it
• Signal Processing — 11 citations into it
• Optimization & Training — 10 citations into it
• Representation & Self-Supervised Learning — 10 citations into it

Whom B. Meyer trusts overall

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

1. Yoshua Bengio
2. Alex Graves
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Ilya Sutskever
7. Diederik P. Kingma
8. J. Urgen Schmidhuber
9. Ruslan Salakhutdinov
10. Kaiming He

Who trusts B. Meyer overall

1. Andrés Camero
2. Dimitrios Stamoulis

Papers from B. Meyer's perspective

Ordered by how strongly the researchers B. Meyer 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Surprisal-Triggered Conditional Computation with Neural Networks (2020) — 6 citations
• Neural networks designing neural networks: Multi-objective hyper-parameter optimization (2016) — 104 citations