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Xiaoling Lu

3 accepted papers

2025

MIHC: Multi-View Interpretable Hypergraph Neural Networks with Information Bottleneck for Chip Congestion Prediction

NeurIPS 2025poster

With AI advancement and increasing circuit complexity, efficient chip design through Electronic Design Automation (EDA) is critical. Fast and accurate congestion prediction in chip layout and routing can significantly enhance automated design performance. Existing congestion modeling methods are lim…

Cited by 0SourceScholar
2024

A Graph-based Representation Framework for Trajectory Recovery via Spatiotemporal Interval-Informed Seq2Seq

IJCAI 2024poster

The prevalent issue in urban trajectory data usage, notably in low-sample rate datasets, revolves around the accuracy of travel time estimations, traffic flow predictions, and trajectory similarity measurements. Conventional methods, often relying on simplistic mixes of static road networks and raw…

2024

Conjugate Bayesian Two-step Change Point Detection for Hawkes Process

NeurIPS 2024poster

The Bayesian two-step change point detection method is popular for the Hawkes process due to its simplicity and intuitiveness. However, the non-conjugacy between the point process likelihood and the prior requires most existing Bayesian two-step change point detection methods to rely on non-conjugat…