Christine Payne

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Computer Vision and Pattern Recognition — 38 citations into it
• Signal Processing — 38 citations into it
• Generative Models — 37 citations into it
• Speech & Audio — 28 citations into it
• Natural Language Processing — 13 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Christine Payne trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Aäron van den Oord
4. Yoshua Bengio
5. Ilya Sutskever
6. Oriol Vinyals
7. Alex Krizhevsky
8. Ruslan Salakhutdinov
9. Alex Graves
10. Jimmy Ba

Papers from Christine Payne's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Jukebox: A Generative Model for Music (2020) — 984 citations