Jennifer Williams

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it
• Signal Processing — 21 citations into it
• Speech & Audio — 18 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Jennifer Williams trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Aäron van den Oord
2. Junichi Yamagishi
3. Suyoun Kim
4. Oriol Vinyals
5. Diederik P. Kingma
6. Geoffrey E. Hinton
7. Yi Zhao
8. Hirofumi Inaguma
9. Gregory Sell
10. Christophe Veaux

Papers from Jennifer Williams's perspective

Ordered by how strongly the researchers Jennifer Williams trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Improved Prosody from Learned F0 Codebook Representations for VQ-VAE Speech Waveform Reconstruction (2020) — 21 citations
• Learning Disentangled Phone and Speaker Representations in a Semi-Supervised VQ-VAE Paradigm (2020) — 27 citations