Haoteng Yin

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 20

Top Topics

Graph Representation

Diffusion Models

Top Venues

Proc. VLDB Endow.

Publications

Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW (2024)
Wei Xiang, Haoteng Yin, He Wang, Xiaogang Jin
SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents. AAAI (2024)
Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. 2024 (2024)
Wei Xiang, Haoteng Yin, He Wang, Xiaogang Jin
SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents. CoRR (2024)
Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR (2023)
Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR (2023)
Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 16 (11) (2023)
Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. CoRR (2023)
Prasita Mukherjee, Haoteng Yin
OCTAL: Graph Representation Learning for LTL Model Checking. CoRR (2023)
Prasita Mukherjee, Haoteng Yin, Susheel Suresh, Tiark Rompf
OCTAL: Graph Representation Learning for LTL Model Checking. CoRR (2022)
Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 15 (11) (2022)
Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. CoRR (2022)
Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. CoRR (2022)
Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. NeurIPS (2022)
Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. ICLR (2022)
Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR (2022)
Haoteng Yin, Yanbang Wang, Pan Li
Revisit graph neural networks and distance encoding in a practical view. CoRR (2020)
Bing Yu, Haoteng Yin, Zhanxing Zhu
ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling. CoRR (2019)
Bing Yu, Haoteng Yin, Zhanxing Zhu
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. IJCAI (2018)
Bing Yu, Haoteng Yin, Zhanxing Zhu
Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting. CoRR (2017)