Felicia S. C. Lim
Signal Processing · 2017–2021
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 63 citations into it; #1,595 of 7,572 by trust here, #1,055 by citations
- Speech & Audio — 45 citations into it; #354 of 1,076 by trust here, #325 by citations
- Computer Vision and Pattern Recognition — 36 citations into it; #12,727 of 21,575 by trust here, #7,340 by citations
- Artificial Intelligence — 35 citations into it; #13,565 of 35,345 by trust here, #13,163 by citations
- Generative Models — 20 citations into it; #1,531 of 1,956 by trust here, #1,110 by citations
- Cognitive Neuroscience — 7 citations into it
- Computational Mechanics — 7 citations into it
- Evaluation & Benchmarks — 7 citations into it; #2,375 of 3,147 by trust here, #2,743 by citations
Whom Felicia S. C. Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Aäron van den Oord
- Per Hedelin
- Andrew Hines
- Oriol Vinyals
- Alan McCree
- Diederik P. Kingma
- Geoffrey E. Hinton
- Nal Kalchbrenner
- Yoshua Bengio
- W. Kleijn
Who trusts Felicia S. C. Lim overall
- Jean-Marc Valin
- Jan Skoglund
- Haici Yang
- Neil Zeghidour
- Jonah Casebeer
- Alexandre D'efossez
- Hubert Siuzdak
- Wootaek Lim
- Ahmed Omran
- Jade Copet
Papers from Felicia S. C. Lim's perspective
Ordered by how strongly the researchers Felicia S. C. Lim 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- GENERATIVE ADVERSARIAL NETS
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Wavenet Based Low Rate Speech Coding (2017) — 154 citations
- ViSQOL v3: An Open Source Production Ready Objective Speech and Audio Metric (2020) — 229 citations
- Robust Low Rate Speech Coding Based on Cloned Networks and Wavenet (2020) — 13 citations
- Low Bit-rate Speech Coding with VQ-VAE and a WaveNet Decoder (2019) — 140 citations
- Generative Speech Coding with Predictive Variance Regularization (2021) — 79 citations