Xinwang Liu
Computer Vision and Pattern Recognition · 2011–2022
A researcher in the Science corpus: 13 papers; trusts 962 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 384 citations into it; #6,822 of 21,575 by trust here, #4,286 by citations
- Artificial Intelligence — 312 citations into it; #9,891 of 35,345 by trust here, #5,682 by citations
- Management Science and Operations Research — 60 citations into it; #4,399 of 11,946 by trust here, #8,062 by citations
- Representation & Self-Supervised Learning — 53 citations into it
- Model Architectures — 40 citations into it
- Media Technology — 34 citations into it
- Graph Learning — 24 citations into it
- Statistics and Probability — 24 citations into it; #5,573 of 12,932 by trust here, #10,275 by citations
Whom Xinwang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zeshui Xu
- Geoffrey E. Hinton
- Diederik P. Kingma
- Kaiming He
- Ross B. Girshick
- Yann LeCun
- Alex Krizhevsky
- Yoshua Bengio
- Christian Szegedy
- David G. Lowe
Who trusts Xinwang Liu overall
- Peide Liu
- Harish Garg
- Mircea Cimpoi
- Yue Liu
- Zongbo Han
- Zeeshan Ali
- Subhransu Maji
- Ava Vali
- Changqing Zhang
- Peng Ye
Papers from Xinwang Liu's perspective
Ordered by how strongly the researchers Xinwang Liu 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Deep Learning for Generic Object Detection: A Survey (2018) — 2,829 citations
- In defense of soft-assignment coding (2011) — 492 citations
- Improved Deep Embedded Clustering with Local Structure Preservation (2017) — 1,034 citations
- Intuitionistic Fuzzy Information Aggregation Using Einstein Operations (2012) — 379 citations
- Understand Dynamic Regret with Switching Cost for Online Decision Making (2019) — 15 citations
- A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal (2022) — 311 citations
- Scalable Multi-view Subspace Clustering with Unified Anchors (2021) — 332 citations
- Deep Graph Clustering via Dual Correlation Reduction (2021) — 320 citations
- Fast Parameter-Free Multi-View Subspace Clustering With Consensus Anchor Guidance (2021) — 427 citations
- Late Fusion Incomplete Multi-view Clustering (2018) — 346 citations
- Deep Clustering with Convolutional Autoencoders (2017) — 538 citations
- Learning Approximate Stochastic Transition Models (2017) — 25 citations
- An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment (2017) — 563 citations