Pixel Deconvolutional Networks. - Hongyang Gao; Hao Yuan 001; Zhengyang Wang; Shuiwang Ji (CoRR, 2017)

Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods. - Hao Yuan 001; Yongjun Chen; Xia Hu 001; Shuiwang Ji (AAAI, 2019)

Learning Local and Global Multi-context Representations for Document Classification. - Yi Liu 059; Hao Yuan 001; Shuiwang Ji (ICDM, 2019)

Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. - Hao Yuan 001; Na Zou 001; Shaoting Zhang 001; Hanchuan Peng; Shuiwang Ji (ICDM, 2019)

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions. - Zhengyang Wang; Hao Yuan 001; Shuiwang Ji (SDM, 2019)

XFake: Explainable Fake News Detector with Visualizations. - Fan Yang 023; Shiva K. Pentyala; Sina Mohseni; Mengnan Du; Hao Yuan 001; Rhema Linder; Eric D. Ragan; Shuiwang Ji; Xia (Ben) Hu (WWW, 2019)

Computational modeling of cellular structures using conditional deep generative networks. - Hao Yuan 001; Lei Cai; Zhengyang Wang; Xia Hu 001; Shaoting Zhang 001; Shuiwang Ji (Bioinform., 2019)

Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images. - Yi Liu 059; Hao Yuan 001; Zhengyang Wang; Shuiwang Ji (CoRR, 2019)

Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis. - Hanzi Mao; Xi Liu 011; Nick Duffield; Hao Yuan 001; Shuiwang Ji; Binayak P. Mohanty (ICDM, 2020)

StructPool: Structured Graph Pooling via Conditional Random Fields. - Hao Yuan 001; Shuiwang Ji (ICLR, 2020)

Deep Learning of High-Order Interactions for Protein Interface Prediction. - Yi Liu 059; Hao Yuan 001; Lei Cai; Shuiwang Ji (KDD, 2020)

XGNN: Towards Model-Level Explanations of Graph Neural Networks. - Hao Yuan 001; Jiliang Tang; Xia Hu 001; Shuiwang Ji (KDD, 2020)

Pixel Transposed Convolutional Networks. - Hongyang Gao; Hao Yuan 001; Zhengyang Wang; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Global Pixel Transformers for Virtual Staining of Microscopy Images. - Yi Liu 059; Hao Yuan 001; Zhengyang Wang; Shuiwang Ji (IEEE Trans. Medical Imaging, 2020)

On Explainability of Graph Neural Networks via Subgraph Explorations. - Hao Yuan 001; Haiyang Yu 005; Jie Wang 005; Kang Li 004; Shuiwang Ji (ICML, 2021)

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks. - Hao Yuan 001; Shuiwang Ji (CoRR, 2021)

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks. - Meng Liu 015; Cong Fu 003; Xuan Zhang; Limei Wang; Yaochen Xie; Hao Yuan 001; Youzhi Luo; Zhao Xu 005; Shenglong Xu; Shuiwang Ji (CoRR, 2021)

DIG: A Turnkey Library for Diving into Graph Deep Learning Research. - Meng Liu 015; Youzhi Luo; Limei Wang; Yaochen Xie; Hao Yuan 001; Shurui Gui; Haiyang Yu 005; Zhao Xu 005; Jingtun Zhang; Yi Liu 059; Keqiang Yan; Haoran Liu; et al. (J. Mach. Learn. Res., 2021)

Interpreting Image Classifiers by Generating Discrete Masks. - Hao Yuan 001; Lei Cai; Xia Hu 001; Jie Wang 005; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping. - Xinyi Xu; Zhengyang Wang; Cheng Deng; Hao Yuan 001; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Explainability in Graph Neural Networks: A Taxonomic Survey. - Hao Yuan 001; Haiyang Yu 005; Shurui Gui; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

FlowX: Towards Explainable Graph Neural Networks via Message Flows. - Shurui Gui; Hao Yuan 001; Jie Wang 005; Qicheng Lao; Kang Li 004; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2024)