Erik Härkönen

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 287 researchers and is trusted by 95 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 85 citations into it; #3,247 of 21,575 by trust here, #3,848 by citations
• Generative Models — 52 citations into it; #422 of 1,956 by trust here, #429 by citations
• Artificial Intelligence — 31 citations into it
• Computer Graphics and Computer-Aided Design — 13 citations into it
• Media Technology — 12 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Model Architectures — 11 citations into it
• Biophysics — 7 citations into it

Whom Erik Härkönen trusts overall

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

1. Tero Karras
2. Diederik P. Kingma
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Kaiming He
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Alec Radford

Who trusts Erik Härkönen overall

1. Yuval Alaluf
2. Peihao Zhu
3. Or Patashnik
4. Rameen Abdal
5. Xingang Pan
6. Yotam Nitzan
7. Eli Shechtman
8. Axel Sauer
9. Zongze Wu
10. Jun-Yan Zhu

Papers from Erik Härkönen's perspective

Ordered by how strongly the researchers Erik Härkönen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• GANSpace: Discovering Interpretable GAN Controls (2020) — 1,034 citations
• Alias-Free Generative Adversarial Networks (2021) — 2,077 citations
• E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles (2019) — 82 citations