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Haoteng Yin
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2020 – today
- 2024
- [j3]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) - [c5]Wei Xiang, Haoteng Yin
, He Wang, Xiaogang Jin:
SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents. AAAI 2024: 6216-6224 - [c4]Tianyi Zhang
, Haoteng Yin
, Rongzhe Wei
, Pan Li
, Anshumali Shrivastava
:
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW 2024: 980-991 - [i12]Wei Xiang, Haoteng Yin, He Wang, Xiaogang Jin:
SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents. CoRR abs/2402.17339 (2024) - 2023
- [j2]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): 2939-2948 (2023) - [i11]Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li:
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. CoRR abs/2303.03379 (2023) - [i10]Prasita Mukherjee, Haoteng Yin:
OCTAL: Graph Representation Learning for LTL Model Checking. CoRR abs/2308.13474 (2023) - [i9]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 abs/2310.15524 (2023) - [i8]Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava:
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR abs/2312.16784 (2023) - 2022
- [j1]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): 2788-2796 (2022) - [c3]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. ICLR 2022 - [c2]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 - [i7]Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li:
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. CoRR abs/2202.13538 (2022) - [i6]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. CoRR abs/2203.00199 (2022) - [i5]Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li:
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR abs/2207.11311 (2022) - [i4]Prasita Mukherjee, Haoteng Yin, Susheel Suresh, Tiark Rompf:
OCTAL: Graph Representation Learning for LTL Model Checking. CoRR abs/2207.11649 (2022) - 2020
- [i3]Haoteng Yin, Yanbang Wang, Pan Li:
Revisit graph neural networks and distance encoding in a practical view. CoRR abs/2011.12228 (2020)
2010 – 2019
- 2019
- [i2]Bing Yu, Haoteng Yin, Zhanxing Zhu:
ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling. CoRR abs/1903.05631 (2019) - 2018
- [c1]Bing Yu, Haoteng Yin
, Zhanxing Zhu:
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. IJCAI 2018: 3634-3640 - 2017
- [i1]Bing Yu, Haoteng Yin, Zhanxing Zhu:
Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting. CoRR abs/1709.04875 (2017)
Coauthor Index
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last updated on 2024-08-14 23:15 CEST by the dblp team
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