DK
Danai Koutra
cs.LGcs.SIcs.AIcs.IRstat.MLcs.CLcs.CYcs.DBphysics.soc-phcs.CR
On Valency
published · living versionsW_efnvzzy5·v1 · currentpublished
Bridging Semantics and Structure: A Theoretically Grounded Framework for Link Prediction on TAGs
with Chen Shao, Ruirui Wang, Tobias Kafer
1 version
Preprints & journals
83 papers in the corpus · 2012–2026Searching for What Matters: Open-Ended Discovery of Multiple Hypotheses with Agentic Data Exploration2610.17874v1 · Sanchit Kabra, Nurendra Choudhary, Jiangshu Du et al.2026 · 0 citationsarXiv
Edge-Level Automorphism in GNNs: A Quantitative Framework and Effective Designs For Link Prediction2609.34729v1 · Chen Shao, Donald Loveland, Tobias Kafer et al.2026 · 0 citationsarXiv
When GNNs Fail: Quantifying and Overcoming Temporal Correlation Volatility in Time Series2608.07333v1 · Chen Shao, Yue Wang, Zhenyi Zhu et al.2026 · 0 citationsEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2026
Preserving Item Semantics for Free: Rethinking Token Initialization in LLM-Based Generative Recommendation2608.07816v1 · Donald Loveland, Liam Collins, Bhuvesh Kumar et al.2026 · 0 citationsarXiv
Formalizing and Mitigating Structural Distortion in LLM Attention for Graph Reasoning2606.15633v2 · Donald Loveland, Puja Trivedi, Ari Weinstein et al.2026 · 0 citationsarXiv
Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discovery2605.04375v2 · Zhenning Yang, Yuhan Chen, Patrick Tser Jern Kon et al.2026 · 0 citationsarXiv
GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs2511.12423v1 · Jiaji Ma, Puja Trivedi, Danai Koutra2025 · 1 citationarXiv
Random Search Neural Networks for Efficient and Expressive Graph Learning2510.22520v1 · Michael Ito, Danai Koutra, Jenna Wiens2025 · 0 citationsarXiv
Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion2510.10849v1 · Donald Loveland, Yao-An Yang, Danai Koutra2025 · 0 citationsarXiv
On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective2505.11318v2 · Donald Loveland, Mingxuan Ju, Tong Zhao et al.2025 · 2 citationsarXiv
Understanding GNNs and Homophily in Dynamic Node Classification2504.20421v1 · Michael Ito, Danai Koutra, Jenna Wiens2025 · 0 citationsarXiv
Learning Laplacian Positional Encodings for Heterophilous Graphs2504.20430v1 · Michael Ito, Jiong Zhu, Dexiong Chen et al.2025 · 0 citationsarXiv
Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics2503.23333v1 · Jing Zhu, Mingxuan Ju, Yozen Liu et al.2025 · 0 citationsarXiv
GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data2410.11235v2 · Jiacheng Lin, Kun Qian, Haoyu Han et al.2024 · 0 citationsarXiv
Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank2410.23300v3 · Donald Loveland, Xinyi Wu, Tong Zhao et al.2024 · 4 citationsarXiv
Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks2410.04287v1 · Donald Loveland, Danai Koutra2024 · 3 citationsarXiv
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks2409.17475v1 · Jiong Zhu, Gaotang Li, Yao-An Yang et al.2024 · 5 citationsarXiv
Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning2406.16321v2 · Jing Zhu, Yuhang Zhou, Shengyi Qian et al.2024 · 3 citationsarXiv
Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation2406.13114v2 · Yuhang Zhou, Jing Zhu, Paiheng Xu et al.2024 · 0 citationsarXiv
LinkGPT: Teaching Large Language Models To Predict Missing Links2406.04640v1 · Zhongmou He, Jing Zhu, Shengyi Qian et al.2024 · 1 citationarXiv
Large Generative Graph Models2406.05109v1 · Yu Wang, Ryan A. Rossi, Namyong Park et al.2024 · 1 citationarXiv
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks2401.03350v2 · Puja Trivedi, Mark Heimann, Rushil Anirudh et al.2024 · 0 citationsarXiv
Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training2312.15520v1 · Charles Dickens, Eddie Huang, Aishwarya Reganti et al.2023 · 13 citationsarXiv
Leveraging Graph Diffusion Models for Network Refinement Tasks2311.17856v1 · Puja Trivedi, Ryan Rossi, David Arbour et al.2023 · 0 citationsarXiv
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning2309.13885v2 · Jing Zhu, Xiang Song, Vassilis N. Ioannidis et al.2023 · 9 citationsarXiv
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks2309.10976v1 · Puja Trivedi, Mark Heimann, Rushil Anirudh et al.2023 · 0 citationsarXiv
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks2306.14375v1 · Gaotang Li, Marlena Duda, Xiang Zhang et al.2023 · 9 citationsarXiv
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks2306.05557v4 · Donald Loveland, Jiong Zhu, Mark Heimann et al.2023 · 1 citationarXiv
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices2306.00899v2 · Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis et al.2023 · 18 citationsarXiv
Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective2305.15611v5 · Gaotang Li, Danai Koutra, Yujun Yan2023 · 0 citationsarXiv
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation2305.09887v1 · Jiong Zhu, Aishwarya Reganti, Edward Huang et al.2023 · 5 citationsarXiv
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias2303.13500v1 · Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan2023 · 6 citationsarXiv
On the Efficacy of Generalization Error Prediction Scoring Functions2303.13589v2 · Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan2023 · 0 citationsarXiv
CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment2208.10682v1 · Jing Zhu, Danai Koutra, Mark Heimann2022 · 7 citationsarXiv
Analyzing Data-Centric Properties for Graph Contrastive Learning2208.02810v3 · Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann et al.2022 · 2 citationsarXiv
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety2207.12615v1 · Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan2022 · 0 citationsarXiv
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods2207.04376v2 · Donald Loveland, Jiong Zhu, Mark Heimann et al.2022 · 5 citationsarXiv
Learning node embeddings via summary graphs: a brief theoretical analysis2207.01189v1 · Houquan Zhou, Shenghua Liu, Danai Koutra et al.2022 · 0 citationsarXiv
Leveraging the Graph Structure of Neural Network Training Dynamics2111.05410v2 · Fatemeh Vahedian, Ruiyu Li, Puja Trivedi et al.2021 · 2 citationsarXiv
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices2111.03220v2 · Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan et al.2021 · 34 citationsarXiv
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation2110.14509v1 · Di Jin, Bunyamin Sisman, Hao Wei et al.2021 · 14 citationsarXiv
Validating dynamicity in resting state fMRI with activation-informed temporal segmentation.34510647 · Duda, Marlena, Koutra, Danai, Sripada, Chandra2022 · 10 citationsHuman brain mapping. 2021;42(17):5718-5735
How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications2106.07767v4 · Jiong Zhu, Junchen Jin, Donald Loveland et al.2021 · 32 citationsarXiv
Relational World Knowledge Representation in Contextual Language Models: A Review2104.05837v2 · Tara Safavi, Danai Koutra2021 · 33 citationsarXiv
Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding2102.13582v1 · Jing Zhu, Xingyu Lu, Mark Heimann et al.2021 · 15 citationsarXiv
A Hidden Challenge of Link Prediction: Which Pairs to Check?2102.07878v1 · Caleb Belth, Alican Buyukcak\ir, Danai Koutra2021 · 2 citationsarXiv
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks2102.06462v8 · Yujun Yan, Milad Hashemi, Kevin Swersky et al.2021 · 190 citationsarXiv
How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation2102.02805v5 · Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra et al.2021 · 2 citationsarXiv
Refining Network Alignment to Improve Matched Neighborhood Consistency2101.08808v1 · Mark Heimann, Xiyuan Chen, Fatemeh Vahedian et al.2021 · 19 citationsarXiv
Towards Understanding and Evaluating Structural Node Embeddings2101.05730v1 · Junchen Jin, Mark Heimann, Di Jin et al.2021 · 1 citationarXiv
Career total: 230 works. 83 are in this corpus.Showing the 50 most recent.
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