Hyeoncheol Cho

Computational Theory and Mathematics · 2018

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 31 citations into it
• Materials Chemistry — 25 citations into it
• Molecular Biology — 19 citations into it
• Computational Chemistry & Drug Discovery — 17 citations into it
• Artificial Intelligence — 10 citations into it
• Graph Learning — 8 citations into it

Whom Hyeoncheol Cho trusts overall

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

1. Brian K. Shoichet
2. David L. Mobley
3. Michaël Defferrard
4. Keyulu Xu
5. S. J. Macalino
6. Bharath Ramsundar
7. Steven M. Kearnes
8. Zhirong Wu
9. Geoffrey E. Hinton
10. Yoshua Bengio

Papers from Hyeoncheol Cho's perspective

Ordered by how strongly the researchers Hyeoncheol Cho 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Enhanced Deep‐Learning Prediction of Molecular Properties via Augmentation of Bond Topology (2018) — 64 citations