Xinjiang Wang
Computer Vision and Pattern Recognition · 2018–2023
A researcher in the Science corpus: 5 papers; trusts 529 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 155 citations into it
- Artificial Intelligence — 125 citations into it; #26,497 of 35,345 by trust here, #13,760 by citations
- Optimization & Training — 48 citations into it; #2,101 of 2,601 by trust here, #1,766 by citations
- Model Architectures — 46 citations into it
- Efficiency & Compression — 44 citations into it
- Evaluation & Benchmarks — 12 citations into it
- Scaling & Learning Theory — 10 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
Whom Xinjiang Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ross B. Girshick
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Shaoqing Ren
- Christian Szegedy
Who trusts Xinjiang Wang overall
- Soham De
- Johannes Klicpera
- Ping Luo
- Jonathan Frankle
- Samuel L. Smith
- Boyi Li
- Jianping Gou
- Kailun Yang
Papers from Xinjiang Wang's perspective
Ordered by how strongly the researchers Xinjiang Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Towards Understanding Regularization in Batch Normalization (2018) — 195 citations
- Online Knowledge Distillation via Collaborative Learning (2020) — 374 citations
- Group Fisher Pruning for Practical Network Compression (2021) — 218 citations
- BiFormer: Vision Transformer with Bi-Level Routing Attention (2023) — 1,025 citations
- Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning (2020) — 24 citations