Yu Wang

Artificial Intelligence · Nature · 2003–2021

A researcher in the Science corpus: 32 papers; trusts 887 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 335 citations into it; #11,368 of 35,345 by trust here, #3,842 by citations
• Computer Vision and Pattern Recognition — 292 citations into it; #7,974 of 21,575 by trust here, #2,648 by citations
• Reinforcement Learning — 119 citations into it
• Electrical and Electronic Engineering — 75 citations into it; #4,685 of 16,539 by trust here, #4,249 by citations
• Optimization & Training — 70 citations into it; #1,339 of 2,601 by trust here, #582 by citations
• Efficiency & Compression — 58 citations into it; #513 of 1,264 by trust here, #323 by citations
• Computational Mechanics — 50 citations into it; #5,530 of 10,001 by trust here, #5,350 by citations
• Representation & Self-Supervised Learning — 48 citations into it

Whom Yu Wang trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Yann LeCun
7. Ross B. Girshick
8. Christian Szegedy
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Yu Wang overall

1. Antonin Chambolle
2. Juyong Zhang
3. Lei Zhang
4. Jen-Hao Rick Chang
5. Weisheng Dong
6. Xianghui Mao
7. Marco Conti
8. Thomas Pock
9. Tianyi Wu
10. Daniel Seichter

Papers from Yu Wang's perspective

Ordered by how strongly the researchers Yu Wang 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Transferrable Prototypical Networks for Unsupervised Domain Adaptation (2019) — 395 citations
• Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training (2017) — 1,676 citations
• How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers? (2020) — 94 citations
• Exploring the Regularity of Sparse Structure in Convolutional Neural Networks (2017) — 258 citations
• Going Deeper with Embedded FPGA Platform for Convolutional Neural Network (2016) — 1,200 citations
• Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems (2021) — 46 citations
• Hu-Fu: Hardware and Software Collaborative Attack Framework Against Neural Networks (2018) — 66 citations
• Routing in vehicular ad hoc networks: A survey (2007) — 1,253 citations
• Global Convergence of ADMM in Nonconvex Nonsmooth Optimization (2015) — 1,382 citations
• Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA (2018) — 491 citations
• The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games (2021) — 2,481 citations
• Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization (2021) — 67 citations
• The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games (2021) — 208 citations
• Progress in the functional modification of graphene/graphene oxide: a review (2020) — 834 citations
• Joint Contrastive Learning with Infinite Possibilities (2020) — 73 citations
• Lednet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation (2019) — 385 citations
• Towards Real-Time Object Detection on Embedded Systems (2018) — 85 citations
• Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models (2018) — 84 citations
• Models for closed-loop supply chain with trade-ins (2017) — 176 citations
• The DArk Matter Particle Explorer mission (2017) — 298 citations