2024
Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models.
Trans. Mach. Learn. Res., 2024
HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases.
CoRR, 2024
AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval.
CoRR, 2024
Context-Aware Clustering using Large Language Models.
CoRR, 2024
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
NetInfoF Framework: Measuring and Exploiting Network Usable Information.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Revisit Orthogonality in Graph-Regularized MLPs.
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.
CoRR, 2023
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization.
CoRR, 2023
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.
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.
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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.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs.
Proc. VLDB Endow., 2022
Efficient and Stable Graph Scattering Transforms via Pruning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
Variational Causal Inference.
CoRR, 2022
Efficient and effective training of language and graph neural network models.
CoRR, 2022
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features.
CoRR, 2022
Graph Neural Networks in Life Sciences: Opportunities and Solutions.
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.
Proceedings of the Tenth International Conference on Learning Representations, 2022
TempoQR: Temporal Question Reasoning over Knowledge Graphs.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection.
IEEE Trans. Knowl. Data Eng., 2021
TempoQR: Temporal Question Reasoning over Knowledge Graphs.
CoRR, 2021
Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features.
CoRR, 2021
Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation.
CoRR, 2021
Unveiling Anomalous Nodes Via Random Sampling and Consensus on Graphs.
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
Graph-Adaptive Semi-Supervised Tracking of Dynamic Processes Over Switching Network Modes.
IEEE Trans. Signal Process., 2020
Tensor Graph Convolutional Networks for Multi-Relational and Robust Learning.
IEEE Trans. Signal Process., 2020
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature.
CoRR, 2020
PanRep: Universal node embeddings for heterogeneous graphs.
CoRR, 2020
Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing.
CoRR, 2020
Pruned Graph Scattering Transforms.
Proceedings of the 8th International Conference on Learning Representations, 2020
Semi-Supervised Learning of Processes Over Multi-Relational Graphs.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Defending Graph Convolutional Networks Against Adversarial Attacks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Unveiling Anomalous Edges and Nominal Connectivity of Attributed Networks.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
2019
Semi-Blind Inference of Topologies and Dynamical Processes Over Dynamic Graphs.
IEEE Trans. Signal Process., 2019
Edge Dithering for Robust Adaptive Graph Convolutional Networks.
CoRR, 2019
GraphSAC: Detecting anomalies in large-scale graphs.
CoRR, 2019
A Recurrent Graph Neural Network for Multi-relational Data.
Proceedings of the IEEE International Conference on Acoustics, 2019
Semi-Supervised Tracking of Dynamic Processes Over Switching Graphs.
Proceedings of the IEEE Data Science Workshop, 2019
Graph Neural Networks for Predicting Protein Functions.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019
Learning Graph Processes with Multiple Dynamical Models.
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.
IEEE Trans. Signal Process., 2018
Semi-Blind Inference of Topologies and Dynamical Processes over Graphs.
CoRR, 2018
Kernel-Based Semi-Supervised Learning Over Multilayer Graphs.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018
Imputation of Coupled Tensors and Graphs.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018
Semi-Blind Inference of Topologies and Signals over Graphs.
Proceedings of the 2018 IEEE Data Science Workshop, 2018
2017
Kernel-Based Reconstruction of Space-Time Functions on Dynamic Graphs.
IEEE J. Sel. Top. Signal Process., 2017
Kernel-based Inference of Functions over Graphs.
CoRR, 2017
Inference of Spatio-Temporal Functions over Graphs via Multi-Kernel Kriged Kalman Filtering.
CoRR, 2017
Semi-parametric graph kernel-based reconstruction.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017
Inference of spatiotemporal processes over graphs via kernel kriged Kalman filtering.
Proceedings of the 25th European Signal Processing Conference, 2017
2016
Coupled graph tensor factorization.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016
Kernel-based reconstruction of space-time functions via extended graphs.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016