Danai Koutra
Artificial Intelligence · 2012–2026
A researcher in the Science corpus: 10 papers; trusts 338 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 261 citations into it; #13,526 of 35,345 by trust here, #7,346 by citations
- Statistical and Nonlinear Physics — 78 citations into it; #3,082 of 10,127 by trust here, #1,207 by citations
- Graph Learning — 74 citations into it
- Natural Language Processing — 74 citations into it
- Computer Vision and Pattern Recognition — 68 citations into it
- Information Systems — 56 citations into it
- Molecular Biology — 36 citations into it
- Computer Networks and Communications — 35 citations into it; #3,174 of 9,886 by trust here, #1,912 by citations
Whom Danai Koutra trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Alec Radford
- Yann LeCun
- Tomas Mikolov
- Alex Graves
- Kaiming He
Who trusts Danai Koutra overall
Papers from Danai Koutra's perspective
Ordered by how strongly the researchers Danai Koutra trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Neural Execution Engines: Learning to Execute Subroutines (2020) — 45 citations
- Graph based anomaly detection and description: a survey (2014) — 1,621 citations
- Relational World Knowledge Representation in Contextual Language Models: A Review (2021) — 63 citations
- Graph Neural Networks with Heterophily (2020) — 406 citations
- RolX: structural role extraction & mining in large graphs (2012) — 479 citations
- Preserving Item Semantics for Free: Rethinking Token Initialization in LLM-Based Generative Recommendation (2026)
- Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks (2021) — 309 citations
- Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs (2020) — 1,400 citations
- GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data (2019) — 121 citations
- Anomaly detection in dynamic networks: a survey (2015) — 385 citations