Vassilis N. Ioannidis

Tom Goldstein

David Wipf

Trans. Mach. Learn. Res., 2024

AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval.

[BibT_eX]

[DOI]

Karthik Subbian

Jure Leskovec

James Zou

CoRR, 2024

Context-Aware Clustering using Large Language Models.

[BibT_eX]

[DOI]

Sindhu Tipirneni

Ravinarayana Adkathimar

Nurendra Choudhary

Gaurush Hiranandani

Rana Ali Amjad

Changhe Yuan

Chandan K. Reddy

CoRR, 2024

STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases.

[BibT_eX]

[DOI]

Karthik Subbian

James Zou

Jure Leskovec

CoRR, 2024

Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.

[BibT_eX]

[DOI]

Jing Zhu

Yuhang Zhou

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning.

[BibT_eX]

[DOI]

Jing Zhu

Xiang Song

Danai Koutra

Christos Faloutsos

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

NetInfoF Framework: Measuring and Exploiting Network Usable Information.

[BibT_eX]

[DOI]

Meng-Chieh Lee

Haiyang Yu

Jian Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs.

[BibT_eX]

[DOI]

Zifeng Wang

Balasubramaniam Srinivasan

Huzefa Rangwala

Rishita Anubhai

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Revisit Orthogonality in Graph-Regularized MLPs.

[BibT_eX]

[DOI]

Hengrui Zhang

Shen Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

SpotTarget: Rethinking the Effect of Target Edges for Link Prediction in Graph Neural Networks.

[BibT_eX]

[DOI]

Jing Zhu

Yuhang Zhou

CoRR, 2023

OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization.

[BibT_eX]

[DOI]

Hengrui Zhang

Shen Wang

CoRR, 2023

Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information.

[BibT_eX]

[DOI]

Yulun Wu

Robert A. Barton

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs.

[BibT_eX]

[DOI]

Hongkuan Zhou

Da Zheng

Israt Nisa

Xiang Song

Proc. VLDB Endow., 2022

Efficient and Stable Graph Scattering Transforms via Pruning.

[BibT_eX]

[DOI]

Siheng Chen

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Variational Causal Inference.

[BibT_eX]

[DOI]

Yulun Wu

Layne C. Price

CoRR, 2022

Efficient and effective training of language and graph neural network models.

[BibT_eX]

[DOI]

CoRR, 2022

A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features.

[BibT_eX]

[DOI]

Tom Goldstein

David Wipf

CoRR, 2022

Graph Neural Networks in Life Sciences: Opportunities and Solutions.

[BibT_eX]

[DOI]

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

TempoQR: Temporal Question Reasoning over Knowledge Graphs.

[BibT_eX]

[DOI]

Prasanna Lakkur Subramanyam

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection.

[BibT_eX]

[DOI]

Ahmed S. Zamzam

Nicholas D. Sidiropoulos

IEEE Trans. Knowl. Data Eng., 2021

TempoQR: Temporal Question Reasoning over Knowledge Graphs.

[BibT_eX]

[DOI]

Prasanna Lakkur Subramanyam

CoRR, 2021

Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features.

[BibT_eX]

[DOI]

CoRR, 2021

Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation.

[BibT_eX]

[DOI]

Cole Hawkins

Soji Adeshina

CoRR, 2021

Unveiling Anomalous Nodes Via Random Sampling and Consensus on Graphs.

[BibT_eX]

[DOI]

Dimitris Berberidis

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Graph-Adaptive Semi-Supervised Tracking of Dynamic Processes Over Switching Network Modes.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2020

Tensor Graph Convolutional Networks for Multi-Relational and Robust Learning.

[BibT_eX]

[DOI]

Antonio G. Marques

IEEE Trans. Signal Process., 2020

COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature.

[BibT_eX]

[DOI]

Colby Wise

CoRR, 2020

PanRep: Universal node embeddings for heterogeneous graphs.

[BibT_eX]

[DOI]

Da Zheng

CoRR, 2020

Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing.

[BibT_eX]

[DOI]

Da Zheng

CoRR, 2020

Pruned Graph Scattering Transforms.

[BibT_eX]

[DOI]

Siheng Chen

Proceedings of the 8th International Conference on Learning Representations, 2020

Semi-Supervised Learning of Processes Over Multi-Relational Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Defending Graph Convolutional Networks Against Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Unveiling Anomalous Edges and Nominal Connectivity of Attributed Networks.

[BibT_eX]

[DOI]

Konstantinos D. Polyzos

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Semi-Blind Inference of Topologies and Dynamical Processes Over Dynamic Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Edge Dithering for Robust Adaptive Graph Convolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2019

GraphSAC: Detecting anomalies in large-scale graphs.

[BibT_eX]

[DOI]

Dimitris Berberidis

CoRR, 2019

A Recurrent Graph Neural Network for Multi-relational Data.

[BibT_eX]

[DOI]

Antonio G. Marques

Proceedings of the IEEE International Conference on Acoustics, 2019

Semi-Supervised Tracking of Dynamic Processes Over Switching Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE Data Science Workshop, 2019

Graph Neural Networks for Predicting Protein Functions.

[BibT_eX]

[DOI]

Antonio G. Marques

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Learning Graph Processes with Multiple Dynamical Models.

[BibT_eX]

[DOI]

Mario Coutino

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Inference of Spatio-Temporal Functions Over Graphs via Multikernel Kriged Kalman Filtering.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2018

Semi-Blind Inference of Topologies and Dynamical Processes over Graphs.

[BibT_eX]

[DOI]

CoRR, 2018

Kernel-Based Semi-Supervised Learning Over Multilayer Graphs.

[BibT_eX]

[DOI]

Panagiotis A. Traganitis

Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Imputation of Coupled Tensors and Graphs.

[BibT_eX]

[DOI]

Ahmed S. Zamzam

Nikolas D. Sidiropoulos

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Semi-Blind Inference of Topologies and Signals over Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017

Kernel-Based Reconstruction of Space-Time Functions on Dynamic Graphs.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2017

Kernel-based Inference of Functions over Graphs.

[BibT_eX]

[DOI]

Athanasios N. Nikolakopoulos

Meng Ma

CoRR, 2017

Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering.

[BibT_eX]

[DOI]

CoRR, 2017

Semi-parametric graph kernel-based reconstruction.

[BibT_eX]

[DOI]

Athanasios N. Nikolakopoulos

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Inference of spatiotemporal processes over graphs via kernel kriged Kalman filtering.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

2016

Coupled graph tensor factorization.

[BibT_eX]

[DOI]

Ahmed S. Zamzam

Nicholas D. Sidiropoulos

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

Kernel-based reconstruction of space-time functions via extended graphs.

[BibT_eX]

[DOI]