Meng Fang

Artificial Intelligence · with Cohn · 2013–2017

A researcher in the Science corpus: 4 papers; trusts 58 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #14,370 of 35,345 by trust here, #16,771 by citations
• Representation & Self-Supervised Learning — 16 citations into it
• Natural Language Processing — 14 citations into it
• Reinforcement Learning — 11 citations into it
• Information Systems — 8 citations into it
• Statistical and Nonlinear Physics — 7 citations into it

Whom Meng Fang trusts overall

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

1. Yoshua Bengio
2. Xifeng Yan
3. Geoffrey E. Hinton
4. Yoon Kim
5. Diederik P. Kingma
6. Lilyana Mihalkova
7. Wenyuan Dai
8. Jimmy Ba
9. Burr Settles
10. Andrew McCallum

Who trusts Meng Fang overall

1. Sebastian Ruder
2. Afshin Rahimi
3. Brielen Madureira
4. Yuan Li
5. Michael Desmond
6. Ivan Vulic
7. David Schlangen
8. Trevor Cohn
9. Garrett Wilson
10. Yuxi Li

Papers from Meng Fang's perspective

Ordered by how strongly the researchers Meng Fang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary (2017) — 74 citations
• Learning how to Active Learn: A Deep Reinforcement Learning Approach (2017) — 313 citations
• TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs (2015) — 46 citations
• Transfer Learning across Networks for Collective Classification (2013) — 55 citations