Klaas Kelchtermans

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #5,777 of 35,345 by trust here, #6,911 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #4,632 of 21,575 by trust here, #4,988 by citations
• Meta & Continual Learning — 10 citations into it
• Optimization & Training — 8 citations into it
• Reinforcement Learning — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it; #776 of 3,145 by trust here, #917 by citations
• Management Science and Operations Research — 6 citations into it

Whom Klaas Kelchtermans trusts overall

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

1. Alex Krizhevsky
2. L. Eon Bottou
3. Andrew W. Moore
4. Shai Shalev-Shwartz
5. Geoffrey E. Hinton
6. Rahaf Aljundi
7. Ilya Sutskever
8. Yoshua Bengio
9. Zhizhong Li
10. Christopher G. Atkeson

Who trusts Klaas Kelchtermans overall

1. Quang Pham
2. Fei Ye
3. Rahaf Aljundi
4. Francesco Pelosin
5. Xisen Jin
6. Jiangpeng He
7. Zhenyi Wang
8. Binh Tang
9. Mohamed Elsayed
10. James Harrison

Papers from Klaas Kelchtermans's perspective

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

Their papers

• Task-Free Continual Learning (2018) — 432 citations