Yanchuan Chang

Orcid: 0000-0002-1376-0311

According to our database1, Yanchuan Chang authored at least 15 papers between 2018 and 2025.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark.
CoRR, May, 2025

Urban Region Representation Learning: A Flexible Approach.
CoRR, March, 2025

K Nearest Neighbor-Guided Trajectory Similarity Learning.
CoRR, February, 2025

Planning-Driven Programming: A Large Language Model Programming Workflow.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Trajectory Similarity Measurement: An Efficiency Perspective.
Proc. VLDB Endow., May, 2024

DualCast: Disentangling Aperiodic Events from Traffic Series with a Dual-Branch Model.
CoRR, 2024

Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond.
CoRR, 2024

Urban Region Representation Learning with Attentive Fusion.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Spatial-temporal Forecasting for Regions without Observations.
Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2023
Effective, Efficient, and Generalizable Algorithms for Trajectory Similarity Queries.
PhD thesis, 2023

Contrastive Trajectory Similarity Learning with Dual-Feature Attention.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Spatial Structure-Aware Road Network Embedding via Graph Contrastive Learning.
Proceedings of the Proceedings 26th International Conference on Extending Database Technology, 2023

2021
Sub-trajectory Similarity Join with Obfuscation.
Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

2020
Packing R-trees with Space-filling Curves: Theoretical Optimality, Empirical Efficiency, and Bulk-loading Parallelizability.
ACM Trans. Database Syst., 2020

2018
Theoretically Optimal and Empirically Efficient R-trees with Strong Parallelizability.
Proc. VLDB Endow., 2018


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