Liyuan Wang
Artificial Intelligence · with Li · 2020–2023
A researcher in the Science corpus: 9 papers; trusts 1,133 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 578 citations into it; #12,163 of 35,345 by trust here, #7,606 by citations
- Computer Vision and Pattern Recognition — 474 citations into it; #8,548 of 21,575 by trust here, #5,754 by citations
- Meta & Continual Learning — 461 citations into it; #386 of 1,041 by trust here, #184 by citations
- Representation & Self-Supervised Learning — 162 citations into it
- Cellular and Molecular Neuroscience — 89 citations into it
- Optimization & Training — 66 citations into it
- Radiology, Nuclear Medicine and Imaging — 59 citations into it
- Neuroscience — 58 citations into it
Whom Liyuan Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Diederik P. Kingma
- Ross B. Girshick
- Yann LeCun
- Ilya Sutskever
- Karen Simonyan
- Alex Graves
Who trusts Liyuan Wang overall
- Hongwei Yan
- Xingxing Zhang
- Liyuan Wang
- Valerio Marsocci
- Da-Wei Zhou
- Jun Zhu
- Kaisheng Ma
- Hang Su
- Gengwei Zhang
- Liangzu Peng
Papers from Liyuan Wang's perspective
Ordered by how strongly the researchers Liyuan Wang 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)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A Comprehensive Survey of Continual Learning: Theory, Method and Application (2023) — 1,490 citations
- Memory Replay with Data Compression for Continual Learning (2022) — 141 citations
- ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning (2021) — 114 citations
- AFEC: Active Forgetting of Negative Transfer in Continual Learning (2021) — 123 citations
- Incorporating neuro-inspired adaptability for continual learning in artificial intelligence (2023) — 101 citations
- SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model (2023) — 207 citations
- Genetic dissection of mutual interference between two consecutive learning tasks in Drosophila (2022) — 3 citations
- CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One (2022) — 78 citations
- Triple-Memory Networks: A Brain-Inspired Method for Continual Learning (2020) — 64 citations