A. van den Oord
Artificial Intelligence · 2018
A researcher in the Science corpus: 1 paper; trusts 204 researchers and is trusted by 3,131 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 34 citations into it; #649 of 35,345 by trust here, #1,066 by citations
- Computer Vision and Pattern Recognition — 23 citations into it; #672 of 21,575 by trust here, #851 by citations
- Natural Language Processing — 17 citations into it
- Representation & Self-Supervised Learning — 17 citations into it; #188 of 3,145 by trust here, #128 by citations
- Generative Models — 6 citations into it
Whom A. van den Oord trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Ilya Sutskever
- Kaiming He
- Jimmy Ba
- Yann LeCun
- Oriol Vinyals
- Nitish Srivastava
Who trusts A. van den Oord overall
- Yu-An Chung
- Yoshua Bengio
- Yonglong Tian
- Alexei Baevski
- Ruslan Salakhutdinov
- Sergey Levine
- Wei-Ning Hsu
- Trevor Darrell
- Rohit Girdhar
- Pieter Abbeel
Papers from A. van den Oord's perspective
Ordered by how strongly the researchers A. van den Oord 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- 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)
Their papers
- Representation Learning with Contrastive Predictive Coding (2018) — 13,907 citations