Christopher van der Heide

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Statistical and Nonlinear Physics — 13 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Statistics and Probability — 8 citations into it
• Generative Models — 5 citations into it

Whom Christopher van der Heide trusts overall

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

1. A. Davie
2. Taye Samuel Faniran
3. Peter K. Friz
4. Mark A. Girolami
5. Qiang Liu
6. Belinda Tzen
7. John C. Duchi
8. Aubrey Hurn
9. T. Chen
10. Diederik P. Kingma

Papers from Christopher van der Heide's perspective

Ordered by how strongly the researchers Christopher van der Heide 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. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. Variational Inference with Normalizing Flows
9. Long Short-Term Memory
10. Auto-Encoding Variational Bayes (International Conference on Learning Representations)

Their papers

• Stochastic Normalizing Flows (2020)