Soji Adeshina

Orcid: 0000-0003-3945-3640

According to our database1, Soji Adeshina authored at least 15 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Hierarchical Compression of Text-Rich Graphs via Large Language Models.
CoRR, 2024

GraphStorm: all-in-one graph machine learning framework for industry applications.
CoRR, 2024

GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

NetInfoF Framework: Measuring and Exploiting Network Usable Information.
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
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization.
CoRR, 2023

PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction.
Proceedings of the ACM Web Conference 2023, 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

2022
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning.
Proceedings of the Learning on Graphs Conference, 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

PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

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

Relational Graph Neural Networks for Fraud Detection in a Super-App environment.
CoRR, 2021


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