Luyu Wang
Artificial Intelligence · 2017–2021
A researcher in the Science corpus: 9 papers; trusts 442 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 189 citations into it; #17,963 of 35,345 by trust here, #13,760 by citations
- Computer Vision and Pattern Recognition — 143 citations into it
- Representation & Self-Supervised Learning — 89 citations into it; #2,169 of 3,145 by trust here, #1,754 by citations
- Signal Processing — 74 citations into it; #5,425 of 7,572 by trust here, #3,099 by citations
- Safety, Robustness & Interpretability — 48 citations into it; #1,577 of 2,251 by trust here, #1,857 by citations
- Speech & Audio — 42 citations into it; #887 of 1,076 by trust here, #885 by citations
- Evaluation & Benchmarks — 39 citations into it
- Natural Language Processing — 31 citations into it; #5,675 of 5,688 by trust here, #3,529 by citations
Whom Luyu Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Alex Graves
- Andrew Zisserman
- Ross B. Girshick
Who trusts Luyu Wang overall
- Alexei Baevski
- Gavin Weiguang Ding
- Qi Liu
- Eduardo Fonseca
- Andrey Guzhov
- Abdel-rahman Mohamed
- Felix Wu
- Mekhail Mustak
- Yu Sun
- Dani Yogatama
Papers from Luyu Wang's perspective
Ordered by how strongly the researchers Luyu 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Broaden Your Views for Self-Supervised Video Learning (2021) — 146 citations
- Multimodal Self-Supervised Learning of General Audio Representations (2021) — 46 citations
- advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch (2019) — 200 citations
- WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset (2021) — 33 citations
- Automatic Selection of t-SNE Perplexity (2017) — 48 citations
- Multi-Format Contrastive Learning of Audio Representations (2021) — 64 citations
- Learning Robust and Multilingual Speech Representations (2020) — 103 citations
- Unsupervised Learning of Efficient and Robust Speech Representations (2019) — 7 citations
- On the Sensitivity of Adversarial Robustness to Input Data Distributions (2018) — 67 citations