Danai Koutra - RankMe

212 papers A* 39A 21B 10Misc 2Journal 102Unranked 32

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents. WWW Mingdai Yang, Nurendra Choudhary, Jiangshu Du, Edward W. Huang, Philip S. Yu, Karthik Subbian, Danai Koutra
2026	A*	`conf`	GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs. AAAI Jiaji Ma, Puja Trivedi, Danai Koutra
2025	A*	`conf`	A Large-scale Training Paradigm for Graph Generative Models. ICLR Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr
2025	J	`jnl`	AgentDR Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents. CoRR Mingdai Yang, Nurendra Choudhary, Jiangshu Du, Edward W. Huang, Philip S. Yu, Karthik Subbian, Danai Koutra
2025	J	`jnl`	Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. CoRR Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, Tong Zhao
2025	—	`conf`	Demystifying the Power of Large Language Models in Graph Generation. NAACL (Findings) Yu Wang, Ryan A. Rossi, Namyong Park, Nesreen K. Ahmed, Danai Koutra, Franck Dernoncourt, Tyler Derr
2025	J	`jnl`	GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs. CoRR Jiaji Ma, Puja Trivedi, Danai Koutra
2025	J	`jnl`	Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion. CoRR Donald Loveland, Yao-An Yang, Danai Koutra
2025	A	`conf`	GraFS: An Integrated GNN-LLM Approach for Inferring Best Functional Substitute Products. CIKM Favour Nerrise, Edward W. Huang, Xiaonan Ji, Karthik Subbian, Danai Koutra
2025	A	`conf`	Learning Laplacian Positional Encodings for Heterophilous Graphs. AISTATS Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens
2025	J	`jnl`	Learning Laplacian Positional Encodings for Heterophilous Graphs. CoRR Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens
2025	A	`conf`	LinkGPT: Leveraging Large Language Models for Enhanced Link Prediction in Text-Attributed Graphs. CIKM Zhongmou He, Jing Zhu, Shengyi Qian, Joyce Chai, Danai Koutra
2025	A	`conf`	MAGNET: A Multi-Agent Graph Neural Network for Efficient Bipartite Task Assignment. AAMAS Donald Loveland, James Usevitch, Zachary Serlin, Danai Koutra, Rajmonda Caceres
2025	A*	`conf`	Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning. CVPR Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra
2025	—	`conf`	Not all Neighbors Agree: Graph Learning Beyond Homophily. GRADES/NDA Danai Koutra
2025	—	`conf`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. KDD (2) Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	J	`jnl`	On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. CoRR Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra
2025	J	`jnl`	Random Search Neural Networks for Efficient and Expressive Graph Learning. CoRR Michael Ito, Danai Koutra, Jenna Wiens
2025	—	`conf`	SKnow-LLM Workshop: Structured Knowledge for Large Language Models. KDD (2) Qi Zhu, Xiusi Chen, Yu Zhang, Soji Adeshina, Costas Mavromatis, Zhen Han, Vassilis N. Ioannidis, Leman Akoglu, Danai Koutra, Huzefa Rangwala
2025	—	`conf`	SciSoc LLM Workshop: Large Language Models for Scientific and Societal Advances. KDD (2) Wei Jin, Lu Cheng, Wenpeng Yin, Xianfeng Tang, Qingsong Wen, Danai Koutra, B. Aditya Prakash, Yan Liu
2025	J	`jnl`	Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation. ACM Trans. Knowl. Discov. Data Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra
2025	—	`conf`	Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective. KDD (2) Gaotang Li, Danai Koutra, Yujun Yan
2025	—	`conf`	Towards Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation. WWW (Companion Volume) Lifu Huang, Danai Koutra, Adithya Kulkarni, Temiloluwa Prioleau, Qingyun Wu, Yujun Yan, Yaoqing Yang, James Zou, Dawei Zhou
2025	A	`conf`	Understanding GNNs and Homophily in Dynamic Node Classification. AISTATS Michael Ito, Danai Koutra, Jenna Wiens
2025	J	`jnl`	Understanding GNNs and Homophily in Dynamic Node Classification. CoRR Michael Ito, Danai Koutra, Jenna Wiens
2025	A*	`conf`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. WWW Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2025	A	`conf`	Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks. SDM Donald Loveland, Danai Koutra
2024	A*	`conf`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. ICLR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	A*	`conf`	Editing Partially Observable Networks via Graph Diffusion Models. ICML Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2024	—	`conf`	Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training. WWW (Companion Volume) Charles Dickens, Edward W. Huang, Aishwarya Reganti, Jiong Zhu, Karthik Subbian, Danai Koutra
2024	J	`jnl`	Large Generative Graph Models. CoRR Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr
2024	J	`jnl`	LinkGPT: Teaching Large Language Models To Predict Missing Links. CoRR Zhongmou He, Jing Zhu, Shengyi Qian, Joyce Chai, Danai Koutra
2024	—	`conf`	Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. EMNLP (Findings) Yuhang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang
2024	J	`jnl`	Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. CoRR Yuhang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang
2024	J	`jnl`	Multimodal Graph Benchmark. CoRR Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra
2024	Misc	`conf`	On Estimating Link Prediction Uncertainty Using Stochastic Centering. ICASSP Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2024	A*	`conf`	On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks. NeurIPS Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra
2024	J	`jnl`	On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks. CoRR Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra
2024	A	`conf`	Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices. WSDM Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra
2024	A*	`conf`	TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning. SIGIR Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos
2024	J	`jnl`	Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. CoRR Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
2024	J	`jnl`	Unified Dense Subgraph Detection: Fast Spectral Theory Based Algorithms. IEEE Trans. Knowl. Data Eng. Wenjie Feng, Shenghua Liu, Danai Koutra, Xueqi Cheng
2024	J	`jnl`	Unleashing the Power of LLMs as Multi-Modal Encoders for Text and Graph-Structured Data. CoRR Jiacheng Lin, Kun Qian, Haoyu Han, Nurendra Choudhary, Tianxin Wei, Zhongruo Wang, Sahika Genc, Edward W. Huang, Sheng Wang, Karthik Subbian, Danai Koutra, Jimeng Sun
2024	J	`jnl`	Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks. CoRR Donald Loveland, Danai Koutra
2023	Misc	`conf`	A Closer Look At Scoring Functions And Generalization Prediction. ICASSP Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	A*	`conf`	A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. ICLR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	A Closer Look at Scoring Functions and Generalization Prediction. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	A*	`conf`	A Provable Framework of Learning Graph Embeddings via Summarization. AAAI Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng
2023	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training. CoRR Charles Dickens, Eddie W. Huang, Aishwarya Reganti, Jiong Zhu, Karthik Subbian, Danai Koutra
2023	J	`jnl`	Heterophily and Graph Neural Networks: Past, Present and Future. IEEE Data Eng. Bull. Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra
2023	A*	`conf`	Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. KDD Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan
2023	J	`jnl`	Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. CoRR Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan
2023	J	`jnl`	Leveraging Graph Diffusion Models for Network Refinement Tasks. CoRR Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part I ECML/PKDD (1) Danai Koutra, Claudia Plant, Manuel Gomez-Rodriguez, Elena Baralis, Francesco Bonchi
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part II ECML/PKDD (2) Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III ECML/PKDD (3) Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part IV ECML/PKDD (4) Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part V ECML/PKDD (5) Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi
2023	—	`conf`	On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. LoG Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
2023	J	`jnl`	On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. CoRR Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
2023	J	`jnl`	Scalable Graph Mining and Learning (Dagstuhl Seminar 23491). Dagstuhl Reports Danai Koutra, Henning Meyerhenke, Ilya Safro, Fabian Brandt-Tumescheit
2023	J	`jnl`	Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation. CoRR Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra
2023	J	`jnl`	Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective. CoRR Yujun Yan, Gaotang Li, Danai Koutra
2023	J	`jnl`	SpotTarget: Rethinking the Effect of Target Edges for Link Prediction in Graph Neural Networks. CoRR Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra
2023	A*	`conf`	The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
2023	J	`jnl`	TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning. CoRR Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos
2022	J	`jnl`	A hidden challenge of link prediction: which pairs to check? Knowl. Inf. Syst. Caleb Belth, Alican Büyükçakir, Danai Koutra
2022	—	`conf`	Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lyu, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He
2022	J	`jnl`	Analyzing Data-Centric Properties for Contrastive Learning on Graphs. CoRR Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022	A*	`conf`	Analyzing Data-Centric Properties for Graph Contrastive Learning. NeurIPS Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022	A*	`conf`	Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. WWW Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra
2022	A	`conf`	CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment. CIKM Jing Zhu, Danai Koutra, Mark Heimann
2022	J	`jnl`	CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment. CoRR Jing Zhu, Danai Koutra, Mark Heimann
2022	J	`jnl`	Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2022	—	`conf`	How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation. CoLLAs Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. Dick
2022	A*	`conf`	How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications. KDD Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra
2022	J	`jnl`	Learning node embeddings via summary graphs: a brief theoretical analysis. CoRR Houquan Zhou, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng
2022	A	`conf`	Leveraging the Graph Structure of Neural Network Training Dynamics. CIKM Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra
2022	A	`conf`	On Generalizing Static Node Embedding to Dynamic Settings. WSDM Di Jin, Sungchul Kim, Ryan A. Rossi, Danai Koutra
2022	J	`jnl`	On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods. CoRR Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
2022	J	`jnl`	Toward Understanding and Evaluating Structural Node Embeddings. ACM Trans. Knowl. Discov. Data Junchen Jin, Mark Heimann, Di Jin, Danai Koutra
2022	A*	`conf`	Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. ICDM Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra
2021	—	`conf`	A Deep Dive Into Understanding The Random Walk-Based Temporal Graph Learning. IISWC Nishil Talati, Di Jin, Haojie Ye, Ajay Brahmakshatriya, Ganesh S. Dasika, Saman P. Amarasinghe, Trevor N. Mudge, Danai Koutra, Ronald G. Dreslinski
2021	J	`jnl`	A Hidden Challenge of Link Prediction: Which Pairs to Check? CoRR Caleb Belth, Alican Büyükçakir, Danai Koutra
2021	J	`jnl`	Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. CoRR Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra
2021	J	`jnl`	Convolutional Neural Network Dynamics: A Graph Perspective. CoRR Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra
2021	J	`jnl`	Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation. CoRR Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra
2021	J	`jnl`	Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation. Proc. VLDB Endow. Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra
2021	A*	`conf`	Graph Neural Networks with Heterophily. AAAI Jiong Zhu, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra
2021	J	`jnl`	Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs. CoRR Jiong Zhu, Junchen Jin, Michael T. Schaub, Danai Koutra
2021	—	`conf`	NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases. EMNLP (1) Tara Safavi, Jing Zhu, Danai Koutra
2021	A	`conf`	Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding. SDM Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra
2021	J	`jnl`	Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding. CoRR Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra
2021	A	`conf`	Refining Network Alignment to Improve Matched Neighborhood Consistency. SDM Mark Heimann, Xiyuan Chen, Fatemeh Vahedian, Danai Koutra
2021	J	`jnl`	Refining Network Alignment to Improve Matched Neighborhood Consistency. CoRR Mark Heimann, Xiyuan Chen, Fatemeh Vahedian, Danai Koutra
2021	—	`conf`	Relational World Knowledge Representation in Contextual Language Models: A Review. EMNLP (1) Tara Safavi, Danai Koutra
2021	J	`jnl`	Relational world knowledge representation in contextual language models: A review. CoRR Tara Safavi, Danai Koutra
2021	J	`jnl`	The Power of Summarization in Graph Mining and Learning: Smaller Data, Faster Methods, More Interpretability. Proc. VLDB Endow. Danai Koutra
2021	J	`jnl`	Towards Understanding and Evaluating Structural Node Embeddings. CoRR Junchen Jin, Mark Heimann, Di Jin, Danai Koutra
2021	J	`jnl`	Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. CoRR Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra
2020	A*	`conf`	A Hidden Challenge of Link Prediction: Which Pairs to Check? ICDM Caleb Belth, Alican Büyükçakir, Danai Koutra
2020	A*	`conf`	Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra
2020	A	`conf`	CONE-Align: Consistent Network Alignment with Proximity-Preserving Node Embedding. CIKM Xiyuan Chen, Mark Heimann, Fatemeh Vahedian, Danai Koutra
2020	—	`conf`	CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. EMNLP (1) Tara Safavi, Danai Koutra
2020	J	`jnl`	CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. CoRR Tara Safavi, Danai Koutra
2020	J	`jnl`	Consistent Network Alignment with Node Embedding. CoRR Xiyuan Chen, Mark Heimann, Fatemeh Vahedian, Danai Koutra
2020	J	`jnl`	Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data. J. Am. Medical Informatics Assoc. Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, Danai Koutra, Michael W. Sjoding, Jenna Wiens
2020	J	`jnl`	Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data. CoRR Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra
2020	B	`conf`	Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns. DSAA Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra
2020	—	`conf`	Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction. EMNLP (1) Tara Safavi, Danai Koutra, Edgar Meij
2020	J	`jnl`	From Static to Dynamic Node Embeddings. CoRR Di Jin, Sungchul Kim, Ryan A. Rossi, Danai Koutra
2020	A	`conf`	G-CREWE: Graph CompREssion With Embedding for Network Alignment. CIKM Kyle Kai Qin, Flora D. Salim, Yongli Ren, Wei Shao, Mark Heimann, Danai Koutra
2020	J	`jnl`	G-CREWE: Graph CompREssion With Embedding for Network Alignment. CoRR Kyle Kai Qin, Flora D. Salim, Yongli Ren, Wei Shao, Mark Heimann, Danai Koutra
2020	J	`jnl`	Generalizing Graph Neural Networks Beyond Homophily. CoRR Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra
2020	J	`jnl`	Generating Negative Commonsense Knowledge. CoRR Tara Safavi, Danai Koutra
2020	J	`jnl`	Graph Neural Networks with Heterophily. CoRR Jiong Zhu, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra
2020	J	`jnl`	Improving the Utility of Knowledge Graph Embeddings with Calibration. CoRR Tara Safavi, Danai Koutra, Edgar Meij
2020	—	`conf`	Message from the workshop chairs. IPDPS Workshops Scott McMillan, Manoj Kumar, Danai Koutra, Mahantesh Halappanavar, Tim Mattson, Antonino Tumeo
2020	A*	`conf`	Mining Persistent Activity in Continually Evolving Networks. KDD Caleb Belth, Xinyi Zheng, Danai Koutra
2020	J	`jnl`	Mining Persistent Activity in Continually Evolving Networks. CoRR Caleb Belth, Xinyi Zheng, Danai Koutra
2020	A*	`conf`	Neural Execution Engines: Learning to Execute Subroutines. NeurIPS Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi
2020	J	`jnl`	Neural Execution Engines: Learning to Execute Subroutines. CoRR Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi
2020	J	`jnl`	On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications. ACM Trans. Knowl. Discov. Data Ryan A. Rossi, Di Jin, Sungchul Kim, Nesreen K. Ahmed, Danai Koutra, John Boaz Lee
2020	—	`conf`	SpecGreedy: Unified Dense Subgraph Detection. ECML/PKDD (1) Wenjie Feng, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng
2020	A	`conf`	Toward Activity Discovery in the Personal Web. WSDM Tara Safavi, Adam Fourney, Robert Sim, Marcin Juraszek, Shane Williams, Ned Friend, Danai Koutra, Paul N. Bennett
2020	A*	`conf`	What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization. WWW Caleb Belth, Xinyi Zheng, Jilles Vreeken, Danai Koutra
2020	J	`jnl`	What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization. CoRR Caleb Belth, Xinyi Zheng, Jilles Vreeken, Danai Koutra
2020	J	`jnl`	t-PINE: tensor-based predictable and interpretable node embeddings. Soc. Netw. Anal. Min. Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam
2019	J	`jnl`	Collaborative topic regression for predicting topic-based social influence. Mach. Learn. Asso Hamzehei, Raymond K. Wong, Danai Koutra, Fang Chen
2019	A	`conf`	Coupled Clustering of Time-Series and Networks. SDM Yike Liu, Linhong Zhu, Pedro A. Szekely, Aram Galstyan, Danai Koutra
2019	A*	`conf`	Distribution of Node Embeddings as Multiresolution Features for Graphs. ICDM Mark Heimann, Tara Safavi, Danai Koutra
2019	J	`jnl`	Fast network discovery on sequence data via time-aware hashing. Knowl. Inf. Syst. Tara Safavi, Chandra Sekhar Sripada, Danai Koutra
2019	J	`jnl`	From Community to Role-based Graph Embeddings. CoRR Ryan A. Rossi, Di Jin, Sungchul Kim, Nesreen K. Ahmed, Danai Koutra, John Boaz Lee
2019	A*	`conf`	GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. KDD Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra
2019	J	`jnl`	Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach. IEEE Trans. Signal Inf. Process. over Networks Pin-Yu Chen, Chun-Chen Tu, Pai-Shun Ting, Ya-Yun Lo, Danai Koutra, Alfred O. Hero III
2019	A*	`conf`	Latent Network Summarization: Bridging Network Embedding and Summarization. KDD Di Jin, Ryan A. Rossi, Eunyee Koh, Sungchul Kim, Anup Rao, Danai Koutra
2019	J	`jnl`	On effective and efficient graph edge labeling. Distributed Parallel Databases Oshini Goonetilleke, Danai Koutra, Kewen Liao, Timos Sellis
2019	A*	`conf`	Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket. ICDM Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller, Danai Koutra
2019	J	`jnl`	SURREAL: Subgraph Robust Representation Learning. Appl. Netw. Sci. Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam
2019	A*	`conf`	Smart Roles: Inferring Professional Roles in Email Networks. KDD Di Jin, Mark Heimann, Tara Safavi, Mengdi Wang, Wei Lee, Lindsay Snider, Danai Koutra
2019	B	`conf`	The Effect of Social Interaction on Facilitating Audience Participation in a Live Music Performance. Creativity & Cognition Sang Won Lee, Aaron Willette, Danai Koutra, Walter S. Lasecki
2019	B	`conf`	When to remember where you came from: node representation learning in higher-order networks. ASONAM Caleb Belth, Fahad Kamran, Donna Tjandra, Danai Koutra
2019	—	`conf`	node2bits: Compact Time- and Attribute-Aware Node Representations for User Stitching. ECML/PKDD (1) Di Jin, Mark Heimann, Ryan A. Rossi, Danai Koutra
2019	J	`jnl`	node2bits: Compact Time- and Attribute-aware Node Representations for User Stitching. CoRR Di Jin, Mark Heimann, Ryan A. Rossi, Danai Koutra
2018	J	`jnl`	Biogeography and environmental conditions shape bacteriophage-bacteria networks across the human microbiome. PLoS Comput. Biol. Geoffrey D. Hannigan, Melissa Beth Duhaime, Danai Koutra, Patrick D. Schloss
2018	J	`jnl`	Bridging Network Embedding and Graph Summarization. CoRR Di Jin, Ryan A. Rossi, Danai Koutra, Eunyee Koh, Sungchul Kim, Anup Rao
2018	A*	`conf`	Career Transitions and Trajectories: A Case Study in Computing. KDD Tara Safavi, Maryam Davoodi, Danai Koutra
2018	J	`jnl`	Career Transitions and Trajectories: A Case Study in Computing. CoRR Tara Safavi, Maryam Davoodi, Danai Koutra
2018	A	`conf`	Fast Flow-based Random Walk with Restart in a Multi-query Setting. SDM Yujun Yan, Mark Heimann, Di Jin, Danai Koutra
2018	B	`conf`	GeoAlign: Interpolating Aggregates over Unaligned Partitions. EDBT Jie Song, Danai Koutra, Murali Mani, H. V. Jagadish
2018	—	`conf`	GeoFlux: Hands-Off Data Integration Leveraging Join Key Knowledge. SIGMOD Conference Jie Song, Danai Koutra, Murali Mani, H. V. Jagadish
2018	J	`jnl`	Graph Summarization Methods and Applications: A Survey. ACM Comput. Surv. Yike Liu, Tara Safavi, Abhilash Dighe, Danai Koutra
2018	—	`conf`	HashAlign: Hash-Based Alignment of Multiple Graphs. PAKDD (3) Mark Heimann, Wei Lee, Shengjie Pan, Kuan-Yu Chen, Danai Koutra
2018	J	`jnl`	Node Representation Learning for Multiple Networks: The Case of Graph Alignment. CoRR Mark Heimann, Haoming Shen, Danai Koutra
2018	A	`conf`	REGAL: Representation Learning-based Graph Alignment. CIKM Mark Heimann, Haoming Shen, Tara Safavi, Danai Koutra
2018	J	`jnl`	Reducing large graphs to small supergraphs: a unified approach. Soc. Netw. Anal. Min. Yike Liu, Tara Safavi, Neil Shah, Danai Koutra
2018	J	`jnl`	SURREAL: SUbgraph Robust REpresentAtion Learning. CoRR Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam
2018	A*	`conf`	Summarizing Graphs at Multiple Scales: New Trends. ICDM Danai Koutra, Jilles Vreeken, Francesco Bonchi
2018	J	`jnl`	t-PINE: Tensor-based Predictable and Interpretable Node Embeddings. CoRR Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam
2018	B	`conf`	t-PNE: Tensor-Based Predictable Node Embeddings. ASONAM Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra, Evangelos E. Papalexakis, Sarah S. Lam
2017	B	`conf`	BotWalk: Efficient Adaptive Exploration of Twitter Bot Networks. ASONAM Amanda J. Minnich, Nikan Chavoshi, Danai Koutra, Abdullah Mueen
2017	J	`jnl`	Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit. CoRR Josh Gardner, Danai Koutra, Jawad Mroueh, Victor Pang, Arya Farahi, Sam Krassenstein, Jared Webb
2017	B	`conf`	Edge Labeling Schemes for Graph Data. SSDBM Oshini Goonetilleke, Danai Koutra, Timos Sellis, Kewen Liao
2017	A*	`conf`	Exploratory Analysis of Graph Data by Leveraging Domain Knowledge. ICDM Di Jin, Danai Koutra
2017	J	`jnl`	Facebook wall posts: a model of user behaviors. Soc. Netw. Anal. Min. Pravallika Devineni, Danai Koutra, Michalis Faloutsos, Christos Faloutsos
2017	—	`book`	Individual and Collective Graph Mining: Principles, Algorithms, and Applications Individual and Collective Graph Mining Danai Koutra, Christos Faloutsos
2017	—	`conf`	Inferring, Summarizing and Mining Multi-source Graph Data. ICDM Workshops Danai Koutra
2017	J	`jnl`	On Summarizing Large-Scale Dynamic Graphs. IEEE Data Eng. Bull. Neil Shah, Danai Koutra, Lisa Jin, Tianmin Zou, Brian Gallagher, Christos Faloutsos
2017	B	`conf`	One Size Does Not Fit All: Profiling Personalized Time-Evolving User Behaviors. ASONAM Pravallika Devineni, Evangelos E. Papalexakis, Danai Koutra, A. Seza Dogruöz, Michalis Faloutsos
2017	J	`jnl`	PERSEUS-HUB: Interactive and Collective Exploration of Large-Scale Graphs. Informatics Di Jin, Aristotelis Leventidis, Haoming Shen, Ruowang Zhang, Junyue Wu, Danai Koutra
2017	A*	`conf`	PNP: Fast Path Ensemble Method for Movie Design. KDD Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos, Jean Bolot
2017	A*	`conf`	Scalable Hashing-Based Network Discovery. ICDM Tara Safavi, Chandra Sekhar Sripada, Danai Koutra
2017	J	`jnl`	Topic-based Social Influence Measurement for Social Networks. Australas. J. Inf. Syst. Asso Hamzehei, Shanqing Jiang, Danai Koutra, Raymond K. Wong, Fang Chen
2016	J	`jnl`	A Graph Summarization: A Survey. CoRR Yike Liu, Abhilash Dighe, Tara Safavi, Danai Koutra
2016	—	`conf`	Coding Varied Behavior Types Using the Crowd. CSCW Companion Jinyeong Yim, Jeel Jasani, Aubrey Henderson, Danai Koutra, Steven Dow, Winnie Leung, Ellen Lim, Mitchell L. Gordon, Jeffrey P. Bigham, Walter S. Lasecki
2016	J	`jnl`	DeltaCon: Principled Massive-Graph Similarity Function with Attribution. ACM Trans. Knowl. Discov. Data Danai Koutra, Neil Shah, Joshua T. Vogelstein, Brian Gallagher, Christos Faloutsos
2016	J	`jnl`	Discovery of "comet" communities in temporal and labeled graphs Com Knowl. Inf. Syst. Miguel Araujo, Stephan Günnemann, Spiros Papadimitriou, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, Danai Koutra
2016	J	`jnl`	Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach. CoRR Pin-Yu Chen, Chun-Chen Tu, Pai-Shun Ting, Ya-Yun Lo, Danai Koutra, Alfred O. Hero III
2016	A	`conf`	On Skewed Multi-dimensional Distributions: the FusionRP Model, Algorithms, and Discoveries. SDM Venkata Krishna Pillutla, Zhanpeng Fang, Pravallika Devineni, Christos Faloutsos, Danai Koutra, Jie Tang
2016	J	`jnl`	PNP: Fast Path Ensemble Method for Movie Design. CoRR Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos, Jean Bolot
2015	J	`jnl`	An Empirical Comparison of the Summarization Power of Graph Clustering Methods. CoRR Yike Liu, Neil Shah, Danai Koutra
2015	A*	`conf`	Events and Controversies: Influences of a Shocking News Event on Information Seeking. WWW Danai Koutra, Paul N. Bennett, Eric Horvitz
2015	J	`jnl`	Graph based anomaly detection and description: a survey. Data Min. Knowl. Discov. Leman Akoglu, Hanghang Tong, Danai Koutra
2015	B	`conf`	If walls could talk: Patterns and anomalies in Facebook wallposts. ASONAM Pravallika Devineni, Danai Koutra, Michalis Faloutsos, Christos Faloutsos
2015	J	`jnl`	Linearized and Single-Pass Belief Propagation. Proc. VLDB Endow. Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos
2015	J	`jnl`	Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool. Proc. VLDB Endow. Danai Koutra, Di Jin, Yuanshi Ning, Christos Faloutsos
2015	J	`jnl`	Summarizing and understanding large graphs. Stat. Anal. Data Min. Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos
2015	A*	`conf`	TimeCrunch: Interpretable Dynamic Graph Summarization. KDD Neil Shah, Danai Koutra, Tianmin Zou, Brian Gallagher, Christos Faloutsos
2014	—	`conf`	Com2: Fast Automatic Discovery of Temporal ('Comet') Communities. PAKDD (2) Miguel Araujo, Spiros Papadimitriou, Stephan Günnemann, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, Danai Koutra
2014	J	`jnl`	Events and Controversies: Influences of a Shocking News Event on Information Seeking. CoRR Danai Koutra, Paul N. Bennett, Eric Horvitz
2014	A*	`conf`	Glance: rapidly coding behavioral video with the crowd. UIST Walter S. Lasecki, Mitchell L. Gordon, Danai Koutra, Malte F. Jung, Steven P. Dow, Jeffrey P. Bigham
2014	J	`jnl`	Graph-based Anomaly Detection and Description: A Survey. CoRR Leman Akoglu, Hanghang Tong, Danai Koutra
2014	—	`conf`	Influence Propagation: Patterns, Model and a Case Study. PAKDD (1) Yibin Lin, Agha Ali Raza, Jay Yoon Lee, Danai Koutra, Roni Rosenfeld, Christos Faloutsos
2014	J	`jnl`	Linearized and Turbo Belief Propagation. CoRR Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos
2014	—	`conf`	Net-Ray: Visualizing and Mining Billion-Scale Graphs. PAKDD (1) U Kang, Jay Yoon Lee, Danai Koutra, Christos Faloutsos
2014	A	`conf`	VOG: Summarizing and Understanding Large Graphs. SDM Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos
2014	J	`jnl`	VoG: Summarizing and Understanding Large Graphs. CoRR Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos
2013	A*	`conf`	BIG-ALIGN: Fast Bipartite Graph Alignment. ICDM Danai Koutra, Hanghang Tong, David M. Lubensky
2013	J	`jnl`	DELTACON: A Principled Massive-Graph Similarity Function CoRR Danai Koutra, Joshua T. Vogelstein, Christos Faloutsos
2013	A	`conf`	DELTACON: A Principled Massive-Graph Similarity Function. SDM Christos Faloutsos, Danai Koutra, Joshua T. Vogelstein
2013	A*	`conf`	Detecting insider threats in a real corporate database of computer usage activity. KDD Ted E. Senator, Henry G. Goldberg, Alex Memory, William T. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon, David A. Bader, Edmond Chow, Irfan A. Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Green, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine, Jay Yoon Lee, Danai Koutra, Christos Faloutsos, Daniel D. Corkill, Lisa Friedland, Amanda Gentzel, David D. Jensen
2013	—	`conf`	Fast anomaly detection despite the duplicates. WWW (Companion Volume) Jay Yoon Lee, U Kang, Danai Koutra, Christos Faloutsos
2013	B	`conf`	Network similarity via multiple social theories. ASONAM Michele Berlingerio, Danai Koutra, Tina Eliassi-Rad, Christos Faloutsos
2013	—	`conf`	Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model. PAKDD (1) Danai Koutra, Vasileios Koutras, B. Aditya Prakash, Christos Faloutsos
2012	J	`jnl`	NetSimile: A Scalable Approach to Size-Independent Network Similarity CoRR Michele Berlingerio, Danai Koutra, Tina Eliassi-Rad, Christos Faloutsos
2012	—	`conf`	OPAvion: mining and visualization in large graphs. SIGMOD Conference Leman Akoglu, Duen Horng Chau, U Kang, Danai Koutra, Christos Faloutsos
2012	A*	`conf`	RolX: structural role extraction & mining in large graphs. KDD Keith Henderson, Brian Gallagher, Tina Eliassi-Rad, Hanghang Tong, Sugato Basu, Leman Akoglu, Danai Koutra, Christos Faloutsos, Lei Li
2012	—	`conf`	TensorSplat: Spotting Latent Anomalies in Time. Panhellenic Conference on Informatics Danai Koutra, Evangelos E. Papalexakis, Christos Faloutsos
2011	—	`conf`	Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms. ECML/PKDD (2) Danai Koutra, Tai-You Ke, U Kang, Duen Horng Chau, Hsing-Kuo Kenneth Pao, Christos Faloutsos