Evren Körpeoglu

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it; #26,546 of 35,345 by trust here, #26,682 by citations
• Graph Learning — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 11 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Statistical and Nonlinear Physics — 10 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it
• Generative Models — 7 citations into it

Whom Evren Körpeoglu trusts overall

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

1. Diederik P. Kingma
2. Max Welling
3. Danilo Jimenez Rezende
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Thomas Kipf
7. Alex Krizhevsky
8. Yann LeCun
9. Laurent Dinh
10. Ali Rahimi

Who trusts Evren Körpeoglu overall

1. Joakim Skarding
2. Yanbang Wang

Papers from Evren Körpeoglu's perspective

Ordered by how strongly the researchers Evren Körpeoglu 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Inductive Representation Learning on Temporal Graphs (2020) — 989 citations
• Self-attention with Functional Time Representation Learning (2019) — 135 citations