Pong Eksombatchai

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it; #12,303 of 35,345 by trust here, #5,638 by citations
• Computer Vision and Pattern Recognition — 25 citations into it
• Graph Learning — 20 citations into it; #286 of 693 by trust here, #152 by citations
• Model Architectures — 12 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Molecular Biology — 5 citations into it

Whom Pong Eksombatchai trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. William L. Hamilton
5. Kaiming He
6. Tomas Mikolov
7. Alex Krizhevsky
8. Ilya Sutskever
9. Diederik P. Kingma
10. Yann LeCun

Who trusts Pong Eksombatchai overall

1. Jiaxuan You
2. Chen Gao
3. Johannes Klicpera
4. William L. Hamilton
5. Xiangnan He
6. Weihua Hu
7. Xiang Wang

Papers from Pong Eksombatchai's perspective

Ordered by how strongly the researchers Pong Eksombatchai 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. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Graph Convolutional Neural Networks for Web-Scale Recommender Systems (2018) — 4,201 citations
• Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems (2019) — 143 citations