Joakim Skarding

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 43 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Statistical and Nonlinear Physics — 28 citations into it
• Graph Learning — 23 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Joakim Skarding trusts overall

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

1. Petter Holme
2. Jure Leskovec
3. Seyed Mehran Kazemi
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Da Xu
7. Diederik P. Kingma
8. William L. Hamilton
9. Alex Krizhevsky
10. Yann LeCun

Papers from Joakim Skarding's perspective

Ordered by how strongly the researchers Joakim Skarding 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. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey (2020) — 336 citations