Hongyang Gao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 50

Top Topics

Power Transmission

Gaussian Process

Graph Representation

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Shibbir Ahmed, Hongyang Gao, Hridesh Rajan
Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment. ICSE (2024)
Benjamin Steenhoek, Hongyang Gao, Wei Le
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection. ICSE (2024)
Zhaoning Yu, Hongyang Gao
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation. CoRR (2024)
Shibbir Ahmed, Hongyang Gao, Hridesh Rajan
Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment. CoRR (2024)
Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models. CoRR (2023)
Siyuan Sun, Hongyang Gao
Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning. NeurIPS (2023)
Yiming Zhu, Cairong Wang, Chenyu Dong, Ke Zhang, Hongyang Gao, Chun Yuan
High-Frequency Normalizing Flow for Image Rescaling. IEEE Trans. Image Process. 32 (2023)
Tiancheng Zhou, Zachary Glanz, Mei Liu, Jiang Bian, Rui Yin, Hongyang Gao
HSELDA: Heterogeneous Sub-Graph Learning for lncRNA-Disease Associations Prediction. BIBM (2023)
Tianxiang Gao, Xiaokai Huo, Hailiang Liu, Hongyang Gao
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models. NeurIPS (2023)
Zhaoning Yu, Hongyang Gao
MotifPiece: A Data-Driven Approach for Effective Motif Extraction and Molecular Representation Learning. CoRR (2023)
Tianxiang Gao, Hongyang Gao
Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths. CoRR (2022)
Zhaoning Yu, Hongyang Gao
MotifExplainer: a Motif-based Graph Neural Network Explainer. CoRR (2022)
Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao
A global convergence theory for deep ReLU implicit networks via over-parameterization. ICLR (2022)
Zhaoning Yu, Hongyang Gao
Molecular Graph Representation Learning via Heterogeneous Motif Graph Construction. CoRR (2022)
Hongyang Gao, Shuiwang Ji
Graph U-Nets. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Zhaoning Yu, Hongyang Gao
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks. ICML (2022)
Tianxiang Gao, Hongyang Gao
On the optimization and generalization of overparameterized implicit neural networks. CoRR (2022)
Benjamin Steenhoek, Wei Le, Hongyang Gao
DeepDFA: Dataflow Analysis-Guided Efficient Graph Learning for Vulnerability Detection. CoRR (2022)
Hongyang Gao, Yi Liu, Xuan Zhang, Shuiwang Ji
Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence. CoRR (2021)
Hongyang Gao, Yi Liu, Shuiwang Ji
Topology-Aware Graph Pooling Networks. IEEE Trans. Pattern Anal. Mach. Intell. 43 (12) (2021)
Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao
A global convergence theory for deep ReLU implicit networks via over-parameterization. CoRR (2021)
Hongyang Gao, Zhengyang Wang, Lei Cai, Shuiwang Ji
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. IEEE Trans. Pattern Anal. Mach. Intell. 43 (8) (2021)
Hongyang Gao, Hao Yuan, Zhengyang Wang, Shuiwang Ji
Pixel Transposed Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 42 (5) (2020)
Hongyang Gao, Lei Cai, Shuiwang Ji
Adaptive Convolutional ReLUs. AAAI (2020)
Kun Li, Junyou Liu, Shijie Zhang, Yang Liu, Peng Wang, Hongyang Gao
Circuit parameter optimization of class E power amplifier for wireless power transmission applications. EITCE (2020)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Kronecker Attention Networks. CoRR (2020)
Meng Liu, Hongyang Gao, Shuiwang Ji
Towards Deeper Graph Neural Networks. CoRR (2020)
Meng Liu, Hongyang Gao, Shuiwang Ji
Towards Deeper Graph Neural Networks. KDD (2020)
Hongyang Gao, Yi Liu, Shuiwang Ji
Topology-Aware Graph Pooling Networks. CoRR (2020)
Yang Liu, Daolian Jiang, Kun Li, Changsong Wang, Yongjian Liu, Lei Wang, Peng Wang, Hongyang Gao
A low-power and low-cost battery equalizing circuit topology. EITCE (2020)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Kronecker Attention Networks. KDD (2020)
Kun Li, Shijie Zhang, Qing Liu, Junyou Liu, Peng Wang, Hongyang Gao, Heming Wang, Hongzheng Wang
Design of Wireless Power Transmission System with Double D-coil. EITCE (2020)
Hongyang Gao, Yongjun Chen, Shuiwang Ji
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations. CoRR (2019)
Hongyang Gao, Shuiwang Ji
Graph Representation Learning via Hard and Channel-Wise Attention Networks. CoRR (2019)
Hongyang Gao, Shuiwang Ji
Graph U-Nets. ICML (2019)
Lei Cai, Hongyang Gao, Shuiwang Ji
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation. SDM (2019)
Hongyang Gao, Shuiwang Ji
Graph U-Nets. CoRR (2019)
Hongyang Gao, Shuiwang Ji
Graph Representation Learning via Hard and Channel-Wise Attention Networks. KDD (2019)
Yongsheng Zhu, Hongyang Gao, Junming Xiao, Boyang Qu, Fanbing Zhu, Lu Yang
Dynamic Multi-Objective Dispatch Considering Wind Power and Electric Vehicles With Probabilistic Characteristics. IEEE Access 7 (2019)
Hongyang Gao, Yongjun Chen, Shuiwang Ji
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations. WWW (2019)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. NeurIPS (2018)
Lei Cai, Zhengyang Wang, Hongyang Gao, Dinggang Shen, Shuiwang Ji
Deep Adversarial Learning for Multi-Modality Missing Data Completion. KDD (2018)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Large-Scale Learnable Graph Convolutional Networks. KDD (2018)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Large-Scale Learnable Graph Convolutional Networks. CoRR (2018)
Yongjun Chen, Hongyang Gao, Lei Cai, Min Shi, Dinggang Shen, Shuiwang Ji
Voxel Deconvolutional Networks for 3D Brain Image Labeling. KDD (2018)
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. CoRR (2018)
Hongyang Gao, Shuiwang Ji
Efficient and Invariant Convolutional Neural Networks for Dense Prediction. CoRR (2017)
Hongyang Gao, Hao Yuan, Zhengyang Wang, Shuiwang Ji
Pixel Deconvolutional Networks. CoRR (2017)
Lei Cai, Hongyang Gao, Shuiwang Ji
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation. CoRR (2017)
Hongyang Gao, Shuiwang Ji
Efficient and Invariant Convolutional Neural Networks for Dense Prediction. ICDM (2017)