Wei Yang Bryan Lim
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 5 papers; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 196 citations into it
- Computer Vision and Pattern Recognition — 95 citations into it
- Electrical and Electronic Engineering — 70 citations into it
- Information Systems — 30 citations into it
- Optimization & Training — 24 citations into it
- Efficiency & Compression — 21 citations into it
- Privacy & Security — 19 citations into it
- Natural Language Processing — 18 citations into it
Whom Wei Yang Bryan Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- H. Brendan McMahan
- Yoshua Bengio
- Kaiming He
- Ilya Sutskever
- Jakub Konecný
- Diederik P. Kingma
- Alex Graves
Who trusts Wei Yang Bryan Lim overall
- Dinh C. Nguyen
- Young Geun Kim
- Ming Ding
- Haftay Gebreslasie Abreha
- Praneeth Vepakomma
- Alysa Ziying Tan
- Chenhao Xu
- Pubudu N. Pathirana
- Mang Ye
- Ahmed Imteaj
Papers from Wei Yang Bryan Lim's perspective
Ordered by how strongly the researchers Wei Yang Bryan Lim trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning (2020) — 26 citations
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey (2019) — 2,306 citations
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach (2020) — 273 citations
- A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges (2022) — 468 citations
- Semantic Communications for Future Internet: Fundamentals, Applications, and Challenges (2022) — 646 citations