Taebum Kim

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 17 citations into it
• Artificial Intelligence — 16 citations into it
• Model Architectures — 5 citations into it

Whom Taebum Kim trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Alex Krizhevsky
4. Kaiming He
5. Yoshua Bengio
6. Sergey Ioffe
7. Ilya Sutskever
8. Christian Szegedy
9. Diederik P. Kingma
10. L. Eon Bottou

Who trusts Taebum Kim overall

1. Lin Wang

Papers from Taebum Kim's perspective

Ordered by how strongly the researchers Taebum Kim trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Knowledge Extraction with No Observable Data (2019) — 109 citations