Discrete-state Continuous-time Diffusion for Graph Generation

no code implementations • 19 May 2024 • Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong

Graph is a prevalent discrete data structure, whose generation has wide applications such as drug discovery and circuit design.

Drug Discovery Graph Generation

Invariant Graph Transformer

no code implementations • 13 Dec 2023 • Zhe Xu, Menghai Pan, Yuzhong Chen, Huiyuan Chen, Yuchen Yan, Mahashweta Das, Hanghang Tong

Based on the self-attention module, our proposed invariant graph Transformer (IGT) can achieve fine-grained, more specifically, node-level and virtual node-level intervention.

Sketching Multidimensional Time Series for Fast Discord Mining

no code implementations • 5 Nov 2023 • Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei zhang, Jeff M. Phillips, Eamonn Keogh

In this work, we propose a sketch for discord mining among multi-dimensional time series.

Anomaly Detection Time Series +1

Denoising Self-attentive Sequential Recommendation

no code implementations • 8 Dec 2022 • Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang

Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.

Denoising Sequential Recommendation

Towards Generating Adversarial Examples on Mixed-type Data

no code implementations • 17 Oct 2022 • Han Xu, Menghai Pan, Zhimeng Jiang, Huiyuan Chen, Xiaoting Li, Mahashweta Das, Hao Yang

The existence of adversarial attacks (or adversarial examples) brings huge concern about the machine learning (ML) model's safety issues.

Anomaly Detection Vocal Bursts Type Prediction