A. Sophia Koepke

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 639 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 106 citations into it; #8,047 of 21,575 by trust here, #9,722 by citations
• Signal Processing — 36 citations into it; #4,909 of 7,572 by trust here, #4,900 by citations
• Artificial Intelligence — 32 citations into it
• Representation & Self-Supervised Learning — 18 citations into it; #2,331 of 3,145 by trust here, #2,910 by citations
• Evaluation & Benchmarks — 10 citations into it
• Generative Models — 10 citations into it
• Optimization & Training — 8 citations into it
• Speech & Audio — 7 citations into it

Whom A. Sophia Koepke trusts overall

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

1. Andrew Zisserman
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Karen Simonyan
6. Kaiming He
7. Yoshua Bengio
8. Ross B. Girshick
9. Yann LeCun
10. Ilya Sutskever

Who trusts A. Sophia Koepke overall

1. Aliaksandr Siarohin
2. Jian Zhao
3. Lele Chen
4. Ayush Kumar Tewari
5. Samuel Albanie
6. Egor Zakharov
7. Tomas Jakab
8. Momina Masood
9. Stéphane Lathuilière
10. Sheng-Yu Wang

Papers from A. Sophia Koepke's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• X2Face: A network for controlling face generation by using images, audio, and pose codes (2018) — 461 citations
• Self-supervised learning of a facial attribute embedding from video (2018) — 141 citations
• Audio Retrieval with Natural Language Queries (2021) — 87 citations