Weike Ye

Materials Chemistry · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 162 citations into it; #8,983 of 11,513 by trust here, #6,473 by citations
• Computer Vision and Pattern Recognition — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Weike Ye trusts overall

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

1. Geoffrey E. Hinton
2. Shyue Ping Ong
3. Yann LeCun
4. Emory M. Chan
5. Geoffroy Hautier
6. Oriol Vinyals
7. Yoshua Bengio
8. L. V. D. van der Maaten
9. Anubhav Jain
10. Diederik P. Kingma

Who trusts Weike Ye overall

1. An Chen
2. Chi Chen
3. Xianglin Liu
4. Johannes Klicpera
5. Xu Zhang
6. Fan-Yun Sun
7. Dane Morgan
8. Rohit Batra

Papers from Weike Ye's perspective

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

Their papers

• Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals (2018) — 1,359 citations
• Deep neural networks for accurate predictions of crystal stability (2017) — 251 citations
• A Critical Review of Machine Learning of Energy Materials (2020) — 478 citations