Missing Data Imputation with Uncertainty-Driven Network
Summary: NOMI: missing-data imputation via uncertainty-aware retrieval + neural-network Gaussian process imputator, explicitly targeting overfitting in deep distribution-modeling methods. Iterative calibration uses posterior uncertainty to refine local neighbor retrieval; EM interpretation gives the framework a neat theoretical footing. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jianwei Wang
- 2. Ying Zhang
- 3. Kai Wang
- 4. Xuemin Lin
- 5. Wenjie Zhang
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,527 | Simpler is More: Efficient Top-K Nearest Neighbors Search on Large Road Networks | 2024 | VLDB | 4.4937074e-05 |
| 8,821 | Efficient Unsupervised Community Search with Pre-trained Graph Transformer | 2024 | VLDB | 4.4417735e-05 |
| 10,029 | Outliers: The Good, the Bad and the Ugly | 2026 | SIGMOD | 4.1945683e-05 |
| 10,644 | Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation | 2025 | VLDB | 4.1945683e-05 |
| 10,675 | On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing | 2025 | VLDB | 4.1945683e-05 |
| 10,744 | DIM-SUM: Dynamic IMputation for Smart Utility Management | 2025 | VLDB | 4.1945683e-05 |
| 10,843 | Machine Learning for Graph Data Management and Query Processing | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,311 | Efficient and Effective Data Imputation with Influence Functions | 2022 | VLDB | 7.2406486e-05 |
| 4,434 | Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process | 2022 | SIGMOD | 6.1929999e-05 |
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