Danai Koutra
20 papers · 2020–2026 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (36) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Keyword Champion
(2)
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Grand Slam
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Triple Crown
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
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Century Club Β· Bronze
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Renaissance Researcher
(5)
ποΈ
Keyword Collector
(93)
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Research topics
Machine Learning
(17)
Deep Learning
(13)
Architectures
(11)
Core Methods
(11)
Artificial Intelligence
(8)
Core AI
(6)
Knowledge & Reasoning
(5)
Application Areas
(5)
Learning Types Β· Machine Learning
(5)
Representation
(5)
Models
(4)
Optimization & Theory
(4)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(2)
Computer Science
(1)
Keywords
graph neural network
(10)
node classification
(4)
link prediction
(3)
graph representation
(2)
contextual language model
(2)
representation learning
(2)
knowledge graph
(2)
large language model
(2)
node embedding
(2)
semi-supervised learning
(1)
epistemic uncertainty
(1)
style transfer
(1)
embedding learning
(1)
self-supervised learning
(1)
benchmark evaluation
(1)
contrastive learning
(1)
domain adaptation
(1)
knowledge representation
(1)
transfer learning
(1)
data augmentation
(1)
Papers
GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs
AAAI 2026
A Large-scale Training Paradigm for Graph Generative Models
ICLR 2025
Demystifying the Power of Large Language Models in Graph Generation
NAACL 2025
Learning Laplacian Positional Encodings for Heterophilous Graphs
AISTATS 2025
Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning
CVPR 2025
Understanding GNNs and Homophily in Dynamic Node Classification
AISTATS 2025
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
ICLR 2024
Editing Partially Observable Networks via Graph Diffusion Models
ICML 2024
Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation
EMNLP 2024
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
NeurIPS 2024
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
ICLR 2023
A Provable Framework of Learning Graph Embeddings via Summarization
AAAI 2023
Analyzing Data-Centric Properties for Graph Contrastive Learning
NeurIPS 2022
Graph Neural Networks with Heterophily
AAAI 2021
NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases
EMNLP 2021
Relational World Knowledge Representation in Contextual Language Models: A Review
EMNLP 2021
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
NeurIPS 2020
CoDEx: A Comprehensive Knowledge Graph Completion Benchmark
EMNLP 2020
Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction
EMNLP 2020
Neural Execution Engines: Learning to Execute Subroutines
NeurIPS 2020