James Foster

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Statistical and Nonlinear Physics — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom James Foster trusts overall

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

1. Diederik P. Kingma
2. Yulia Rubanova
3. T. Chen
4. Hongyuan Mei
5. Belinda Tzen

Who trusts James Foster overall

1. Albert Gu

Papers from James Foster's perspective

Ordered by how strongly the researchers James Foster 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Neural Ordinary Differential Equations
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. PyTorch: An Imperative Style, High-Performance Deep Learning Library
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Neural Controlled Differential Equations for Irregular Time Series (2020) — 758 citations