Wootaek Lim
Signal Processing · 2016–2022
A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 28 citations into it; #4,898 of 7,572 by trust here, #5,570 by citations
- Artificial Intelligence — 26 citations into it
- Speech & Audio — 18 citations into it
- Computer Vision and Pattern Recognition — 15 citations into it
- Natural Language Processing — 10 citations into it
- Experimental and Cognitive Psychology — 9 citations into it; #5,378 of 9,731 by trust here, #7,077 by citations
Whom Wootaek Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Geoffrey E. Hinton
- Tomas Mikolov
- Alex Krizhevsky
- Karen Simonyan
- Yoshua Bengio
- Oriol Vinyals
- Yann LeCun
- Andrew Zisserman
- Diederik P. Kingma
Who trusts Wootaek Lim overall
- Amir Zadeh
- Panagiotis Tzirakis
- Taiba Maijd Wani
- Soujanya Poria
- Percy Liang
- Erik Cambria
- Minghai Chen
- George Trigeorgis
- Teddy Surya Gunawan
- Ido Ariav
Papers from Wootaek Lim's perspective
Ordered by how strongly the researchers Wootaek Lim 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)
- Long Short-Term Memory
- 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)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Neural Feature Predictor and Discriminative Residual Coding for Low-Bitrate Speech Coding (2022) — 9 citations
- Speech emotion recognition using convolutional and Recurrent Neural Networks (2016) — 350 citations