Shuiwang Ji

发表

An accelerated gradient method for trace norm minimization

Jieping Ye, Shuiwang Ji, Jieping Ye, 2009, ICML '09.

3D Convolutional Neural Networks for Human Action Recognition

Ming Yang, Shuiwang Ji, Wei Xu, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information

Michael J. Watts, Haibo He, Giorgio Battistelli, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Smoothed dilated convolutions for improved dense prediction

Zhengyang Wang, Shuiwang Ji, Shuiwang Ji, 2018, Data Mining and Knowledge Discovery.

Image-level and group-level models for Drosophila gene expression pattern annotation

Jieping Ye, Qian Sun, Shuiwang Ji, 2013, BMC Bioinformatics.

Hypergraph spectral learning for multi-label classification

Jieping Ye, Liang Sun, Shuiwang Ji, 2008, KDD.

Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning

Paul Tseng, Jieping Ye, Shuiwang Ji, 2010, SIAM J. Optim..

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

Shuiwang Ji, Wenlu Zhang, Dinggang Shen, 2015, NeuroImage.

Pixel Deconvolutional Networks pdf

Zhengyang Wang, Hao Yuan, Shuiwang Ji, 2017, ArXiv.

Explainability in Graph Neural Networks: A Taxonomic Survey

Shuiwang Ji, Hao Yuan, Haiyang Yu, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Adversarial Attacks and Defenses on Graphs

Jiliang Tang, Shuiwang Ji, Yiqi Wang, 2020, SIGKDD Explor..

Self-Supervised Learning of Graph Neural Networks: A Unified Review

Shuiwang Ji, Yaochen Xie, Zhao Xu, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy

Shuiwang Ji, Jing He, Rongjian Li, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A machine learning approach for the identification of protein secondary structure elements from electron cryo-microscopy density maps.

Dong Si, Jing He, Shuiwang Ji, 2012, Biopolymers.

High-resolution prediction of mouse brain connectivity using gene expression patterns.

Shuiwang Ji, Ahmed Fakhry, Shuiwang Ji, 2015, Methods.

Partial Least Squares

Shuiwang Ji, Jieping Ye, Liang Sun, 2016 .

Generating 3D Molecules for Target Protein Binding

Shuiwang Ji, M. Liu, K. Maruhashi, 2022, ArXiv.

Augmented Equivariant Attention Networks for Electron Microscopy Image Super-Resolution

Shuiwang Ji, Yu Ding, Yaochen Xie, 2020, ArXiv.

Three-dimensional protein shape similarity analysis based on hybrid features.

Shuiwang Ji, Zhong Li, Jiangjiang Yu, 2018, Gene.

FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis

Sethuraman Panchanathan, Jieping Ye, Shuiwang Ji, 2011, Bioinform..

Extracting Shared Subspaces for Multi-label Classificatio n

Shuiwang Ji, Lei Tang, 2008 .

Learning subspace kernels for classification

Jieping Ye, Jianhui Chen, Qi Li, 2008, KDD.

Collaborative MultiView Denoising

Dinggang Shen, Lei Zhang, Yong Wang, 2016 .

BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology

Sean L. Hill, Todd A. Gillette, G. Jefferis, 2022, bioRxiv.

Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks

Shuiwang Ji, M. Liu, Haiyang Yu, 2022, ArXiv.

GOOD: A Graph Out-of-Distribution Benchmark

Shuiwang Ji, Shurui Gui, Xiner Li, 2022, 2206.08452.

Generating 3D Molecules for Target Protein Binding

Shuiwang Ji, M. Liu, K. Maruhashi, 2022, ICML.

ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs

Shuiwang Ji, H. Liu, Limei Wang, 2022, ArXiv.

Spherical Message Passing for 3D Graph Networks

Shuiwang Ji, Bora Oztekin, Limei Wang, 2021, ArXiv.

Back-Propagation: From Fully Connected to Convolutional Layers

Shuiwang Ji, 2019 .

Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification

Shuiwang Ji, Feng Wu, Houqiang Li, 2022, 2206.08150.

Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions

Shuiwang Ji, Bin Li, Jie Wang, 2022, ArXiv.

FlowX: Towards Explainable Graph Neural Networks via Message Flows

Shuiwang Ji, Hao Yuan, Shurui Gui, 2022, ArXiv.

Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions

Shuiwang Ji, Bin Li, Jie Wang, 2022, KDD.

Self-Supervised Representation Learning via Latent Graph Prediction

Shuiwang Ji, Zhao Xu, Yaochen Xie, 2022, ICML.

Trust Evolution Over Time in Explainable AI for Fake News Detection

Shiva K. Pentyala, Shuiwang Ji, Xia Hu, 2020 .

Joint Dimensionality Reduction and Classification

Shuiwang Ji, Jieping Ye, Liang Sun, 2016 .

ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs

Shuiwang Ji, H. Liu, Limei Wang, 2022, Neural Information Processing Systems.

A N A UTOREGRESSIVE F LOW M ODEL FOR 3D M OLEC ULAR G EOMETRY G ENERATION FROM S CRATCH

Shuiwang Ji, Youzhi Luo, 2022 .

Learning Protein Representations via Complete 3D Graph Networks

Shuiwang Ji, Limei Wang, Yi Liu, 2022, ArXiv.

GOOD: A Graph Out-of-Distribution Benchmark

Shuiwang Ji, Shurui Gui, Xiner Li, 2022, NeurIPS.

ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs

Shuiwang Ji, H. Liu, Limei Wang, 2022, NeurIPS.

Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification

Shuiwang Ji, Feng Wu, Houqiang Li, 2022, ArXiv.

Deep Neural Networks with Knowledge Instillation

Fan Yang, Shuiwang Ji, Xia Hu, 2020, SDM.

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Shuiwang Ji, M. Liu, Haoran Liu, 2022, 2210.05782.

Periodic Graph Transformers for Crystal Material Property Prediction

Shuiwang Ji, Yi Liu, Yu-Ching Lin, 2022, NeurIPS.

Self-Supervised Representation Learning via Latent Graph Prediction

Shuiwang Ji, Zhao Xu, Yaochen Xie, 2022, ICML.

GraphFM: Improving Large-Scale GNN Training via Feature Momentum

Tianbao Yang, Shuiwang Ji, Haiyang Yu, 2022, ICML.

A deep transfer learning approach for improved post-traumatic stress disorder diagnosis

Shuiwang Ji, Jiang Li, Lemin Xiao, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems

Shuiwang Ji, Shenglong Xu, Xuan Zhang, 2022, ArXiv.

Task-Agnostic Graph Explanations

Nikhil S. Rao, Shuiwang Ji, S. Katariya, 2022, NeurIPS.

Spherical Message Passing for 3D Graph Networks

Shuiwang Ji, Bora Oztekin, Limei Wang, 2021, ArXiv.

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding

Stan Z. Li, Shuiwang Ji, Haitao Lin, 2022, ArXiv.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

Shuiwang Ji, 2013, BMC Bioinformatics.

Towards Deeper Graph Neural Networks

Shuiwang Ji, Meng Liu, Hongyang Gao, 2020, KDD.

Voxel Deconvolutional Networks for 3D Brain Image Labeling

Dinggang Shen, Shuiwang Ji, Min Shi, 2018, KDD.

A Robust Deep Model for Improved Classification of AD/MCI Patients

Dinggang Shen, Jiang Li, Feng Li, 2015, IEEE Journal of Biomedical and Health Informatics.

Large-Scale Learnable Graph Convolutional Networks

Zhengyang Wang, Shuiwang Ji, Hongyang Gao, 2018, KDD.

Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning

Jieping Ye, Zhi-Hua Zhou, Ying-Xin Li, 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A bag-of-words approach for Drosophila gene expression pattern annotation

Jieping Ye, Zhi-Hua Zhou, Ying-Xin Li, 2009, BMC Bioinformatics.

Multi-label Multiple Kernel Learning

Jieping Ye, Rong Jin, Liang Sun, 2008, NIPS.

Automated annotation of Drosophila gene expression patterns using a controlled vocabulary

Jieping Ye, Rong Jin, Liang Sun, 2008, Bioinform..

Pixel Transposed Convolutional Networks

Zhengyang Wang, Hao Yuan, Shuiwang Ji, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Adversarial Attacks and Defenses on Graphs

Charu Aggarwal, Shuiwang Ji, Jiliang Tang, 2021, SIGKDD Explor..

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain

Jieping Ye, Ravi Mukkamala, Shuiwang Ji, 2015, BMC Bioinformatics.

Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

Jieping Ye, Qian Sun, Shuiwang Ji, 2015, IEEE Transactions on Big Data.

Feature Selection Based on Structured Sparsity: A Comprehensive Study

Tieniu Tan, Zhenan Sun, Dacheng Tao, 2017, IEEE Transactions on Neural Networks and Learning Systems.

Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis

Shuiwang Ji, N. Duffield, B. Mohanty, 2020, 2020 IEEE International Conference on Data Mining (ICDM).

XGNN: Towards Model-Level Explanations of Graph Neural Networks

Shuiwang Ji, Jiliang Tang, Xia Hu, 2020, KDD.

Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods

Yongjun Chen, Hao Yuan, Shuiwang Ji, 2019, AAAI.

Learning Hierarchical Protein Representations via Complete 3D Graph Networks

Shuiwang Ji, Limei Wang, Yi Liu, 2022, ICLR.

Deep Learning of High-Order Interactions for Protein Interface Prediction

Shuiwang Ji, Yi Liu, Lei Cai, 2020, KDD.

Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization pdf

Jieping Ye, Shuiwang Ji, Jun Liu, 2009, UAI.

Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection

Jieping Ye, Shuiwang Ji, Jieping Ye, 2008, IEEE Transactions on Neural Networks.

A shared-subspace learning framework for multi-label classification

Jieping Ye, Lei Tang, Shuiwang Ji, 2010, TKDD.

Drosophila gene expression pattern annotation using sparse features and term-term interactions

Jieping Ye, Zhi-Hua Zhou, Ying-Xin Li, 2009, KDD.

Discriminant Analysis for Dimensionality Reduction: An Overview of Recent Developments

Jieping Ye, Shuiwang Ji, Jieping Ye, 2010 .

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery.

Shuiwang Ji, Zhao Xu, Lei Cai, 2020, Bioinformatics.

Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising pdf

Shuiwang Ji, Yaochen Xie, Zhengyang Wang, 2020, NeurIPS.

Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation

Shuiwang Ji, Lei Cai, Hongyang Gao, 2017, SDM.

Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis

Dinggang Shen, Jiang Li, Heung-Il Suk, 2014, MICCAI.

Automated Data Augmentations for Graph Classification

Shuiwang Ji, Youzhi Luo, Kanji Uchino, 2022, ICLR.

How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and its Kernel Version?

Xindong Wu, Zhenan Sun, Jie Gui, 2014, IEEE Transactions on Circuits and Systems for Video Technology.

Robust Deep Learning for Improved Classification of AD/MCI Patients

Dinggang Shen, Jiang Li, Feng Li, 2014, MLMI.

Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming

Jieping Ye, Jianhui Chen, Shuiwang Ji, 2007, KDD '07.

Graph U-Nets

Shuiwang Ji, Hongyang Gao, Shuiwang Ji, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence pdf

Shuiwang Ji, Yi Liu, Hongyang Gao, 2021, ArXiv.

Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution

Shuiwang Ji, Feng Wu, Bin Li, 2023, ArXiv.

Evolutionary soft co-clustering: formulations, algorithms, and applications

Andrey N. Chernikov, Daming Feng, Shuiwang Ji, 2015, Data Mining and Knowledge Discovery.

Multi-class Discriminant Kernel Learning via Convex Programming

Jieping Ye, Jianhui Chen, Shuiwang Ji, 2008, J. Mach. Learn. Res..

A new perspective on building efficient and expressive 3D equivariant graph neural networks

Shuiwang Ji, Yuanqi Du, Weitao Du, 2023, ArXiv.

A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis pdf

Shuiwang Ji, Yi Liu, Shuiwang Ji, 2021, ArXiv.

An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch

Shuiwang Ji, Youzhi Luo, 2022, ICLR.

Frontiers of Graph Neural Networks with DIG

Shuiwang Ji, Yaochen Xie, Haiyang Yu, 2022, KDD.

FlowX: Towards Explainable Graph Neural Networks via Message Flows

Shuiwang Ji, Hao Yuan, Shurui Gui, 2022, ArXiv.

DIG: A Turnkey Library for Diving into Graph Deep Learning Research pdf

Shuiwang Ji, Hao Yuan, Shurui Gui, 2021, J. Mach. Learn. Res..

Topology-Aware Graph Pooling Networks pdf

Shuiwang Ji, Yi Liu, Hongyang Gao, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On Explainability of Graph Neural Networks via Subgraph Explorations

Shuiwang Ji, Hao Yuan, Haiyang Yu, 2021, ICML.

GraphDF: A Discrete Flow Model for Molecular Graph Generation

Shuiwang Ji, Youzhi Luo, Keqiang Yan, 2021, ICML.

GraphEBM: Molecular Graph Generation with Energy-Based Models

Shuiwang Ji, Bora Oztekin, Meng Liu, 2021, ArXiv.

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs pdf

Shuiwang Ji, Maho Nakata, Youzhi Luo, 2021, ArXiv.

Graph Representation Learning via Hard and Channel-Wise Attention Networks

Shuiwang Ji, Hongyang Gao, Shuiwang Ji, 2019, KDD.

Interpreting Image Classifiers by Generating Discrete Masks

Jie Wang, Shuiwang Ji, Xia Hu, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

StructPool: Structured Graph Pooling via Conditional Random Fields

Shuiwang Ji, Hao Yuan, Shuiwang Ji, 2020, ICLR.

XFake: Explainable Fake News Detector with Visualizations

Fan Yang, Hao Yuan, Eric D. Ragan, 2019, WWW.

Adaptive diffusion kernel learning from biological networks for protein function prediction

Jieping Ye, Liang Sun, Shuiwang Ji, 2008, BMC Bioinformatics.

On Explainability of Graph Neural Networks via Subgraph Explorations pdf

Kang Li, Shuiwang Ji, Hao Yuan, 2021, International Conference on Machine Learning.

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks pdf

Shuiwang Ji, Hao Yuan, Shuiwang Ji, 2021, ArXiv.

A Multi-Scale Approach for Graph Link Prediction

Shuiwang Ji, Lei Cai, Shuiwang Ji, 2020, AAAI.

Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis

Jieping Ye, Liang Sun, Shuiwang Ji, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Finite Domain Constraint Solver Learning

Jieping Ye, Shuiwang Ji, Liang Sun, 2009, IJCAI.

Non-Local U-Nets for Biomedical Image Segmentation

Dinggang Shen, Shuiwang Ji, Na Zou, 2020, AAAI.

Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction

Shuiwang Ji, Tao Zeng, Hanchuan Peng, 2017, IEEE Transactions on Medical Imaging.

Global Pixel Transformers for Virtual Staining of Microscopy Images

Shuiwang Ji, Yi Liu, Hao Yuan, 2019, IEEE Transactions on Medical Imaging.

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence

Tianbao Yang, Shuiwang Ji, Zhao Xu, 2021, NeurIPS.

Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci

Shuiwang Ji, Xiaoping Hu, Ahmed Fakhry, 2014, Brain Structure and Function.

Multiview Partitioning via Tensor Methods

Bart De Moor, Wolfgang Glänzel, Shuiwang Ji, 2013, IEEE Transactions on Knowledge and Data Engineering.

Line Graph Neural Networks for Link Prediction pdf

Jie Wang, Shuiwang Ji, Jundong Li, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Non-Local Graph Neural Networks

Shuiwang Ji, Meng Liu, Zhengyang Wang, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Linear Dimensionality Reduction for Multi-label Classification

Jieping Ye, Shuiwang Ji, 2009, IJCAI.

Deep Adversarial Learning for Multi-Modality Missing Data Completion

Dinggang Shen, Zhengyang Wang, Shuiwang Ji, 2018, KDD.

AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter

Shuiwang Ji, Kaize Ding, Jundong Li, 2021, CIKM.

DeepEM3D: approaching human‐level performance on 3D anisotropic EM image segmentation

Bian Wu, Shuiwang Ji, Tao Zeng, 2017, Bioinform..

ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions

Zhengyang Wang, Shuiwang Ji, Hongyang Gao, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs pdf

Jiajun Chen, Shuiwang Ji, Zhanqiu Zhang, 2021, NeurIPS.

Kronecker Attention Networks

Shuiwang Ji, Hongyang Gao, Zhengyang Wang, 2020, KDD.

Dense Transformer Networks pdf

Jun Li, Ian Davidson, Shuiwang Ji, 2017, ArXiv.

Adversarial Graph Disentanglement

Shuiwang Ji, Zhenfeng Zhu, Yao Zhao, 2021, ArXiv.

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

Shuiwang Ji, Shurui Gui, Youzhi Luo, 2023, ArXiv.

Parallel Lasso Screening for Big Data Optimization

Paul M. Thompson, Qingyang Li, Jieping Ye, 2016, KDD.

Structural Graphical Lasso for Learning Mouse Brain Connectivity

Jieping Ye, Qian Sun, Ian Davidson, 2015, KDD.

Sparsity Learning Formulations for Mining Time-Varying Data

Yao Zhao, Zhenfeng Zhu, Shuiwang Ji, 2015, IEEE Transactions on Knowledge and Data Engineering.

Automated Gene Expression Pattern Annotation in the Mouse Brain

Jieping Ye, Shuiwang Ji, Tao Zeng, 2014, Pacific Symposium on Biocomputing.

Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns

Shuiwang Ji, Wenlu Zhang, Rongjian Li, 2014, BMC Bioinformatics.

Integrative analysis of the connectivity and gene expression atlases in the mouse brain

Shuiwang Ji, Houtao Deng, Ahmed Fakhry, 2014, NeuroImage.

Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression

Cheng Pan, Jieping Ye, Zhi-Hua Zhou, 2013, Bioinform..

Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval

Jieping Ye, Zhi-Hua Zhou, Yuan Jiang, 2012, BMC Bioinformatics.

Computational network analysis of the anatomical and genetic organizations in the mouse brain

Shuiwang Ji, Shuiwang Ji, 2011, Bioinform..

Sparsity Learning Formulations for Mining

Yao Zhao, Zhenfeng Zhu, Shuiwang Ji, 2015 .

Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation

Shuiwang Ji, Tao Zeng, Ahmed Fakhry, 2017, IEEE Transactions on Medical Imaging.

Graph Mixup with Soft Alignments

Shuiwang Ji, Meng Liu, Zhimeng Jiang, 2023, ICML.

Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction

Shuiwang Ji, Youzhi Luo, Yi Liu, 2023, 2306.10045.

Development of Xanthene‐Based Fluorescent Dyes: Machine Learning‐Assisted Prediction vs. TD‐DFT Prediction and Experimental Validation

Shuiwang Ji, Shi Xu, Limei Wang, 2021 .

A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection

Fengbo Ren, Shuiwang Ji, Xichuan Zhou, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Multi-View Missing Data Completion

Dinggang Shen, Zhenfeng Zhu, Shuiwang Ji, 2018, IEEE Transactions on Knowledge and Data Engineering.

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Todd A. Gillette, G. Jefferis, A. Sironi, 2023, Nature Methods.

Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction

Hao Yuan, Shuiwang Ji, Hanchuan Peng, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Shuiwang Ji, Meng Liu, Haoran Liu, 2022, ICLR.

Global voxel transformer networks for augmented microscopy pdf

Shuiwang Ji, Zhengyang Wang, Yaochen Xie, 2020, Nature Machine Intelligence.

Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping

Shuiwang Ji, Zhangyang Wang, Xinyi Xu, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A deep transfer learning approach for improved post-traumatic stress disorder diagnosis

Jiang Li, Cai Lei, Roger Xu, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

A sparsity-inducing formulation for evolutionary co-clustering

Shuiwang Ji, Jun Liu, Wenlu Zhang, 2012, KDD.

On Attribution of Recurrent Neural Network Predictions via Additive Decomposition

Fan Yang, Shuiwang Ji, Xia Hu, 2019, WWW.

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks pdf

Shuiwang Ji, Hao Yuan, Yaochen Xie, 2021, ArXiv.

Second-Order Pooling for Graph Neural Networks

Shuiwang Ji, Zhengyang Wang, Shuiwang Ji, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization

Shuiwang Ji, Shurui Gui, Youzhi Luo, 2023, ArXiv.

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Shuiwang Ji, Haiyang Yu, Youzhi Luo, 2023, ArXiv.

Learning Local and Global Multi-context Representations for Document Classification

Hao Yuan, Shuiwang Ji, Yi Liu, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Collaborative Multi-View Denoising

Dinggang Shen, Lei Zhang, Yong Wang, 2016, KDD.

Group Equivariant Fourier Neural Operators for Partial Differential Equations

Shuiwang Ji, Stephan Wojtowytsch, Xuan Zhang, 2023, ArXiv.

Empowering GNNs via Edge-Aware Weisfeiler-Lehman Algorithm

Shuiwang Ji, Haiyang Yu, Meng Liu, 2022, 2206.02059.

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian

Shuiwang Ji, Haiyang Yu, Zhao Xu, 2023, ICML.

Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence pdf

Tianbao Yang, Shuiwang Ji, Youzhi Luo, 2021, ArXiv.

Group Contrastive Self-Supervised Learning on Graphs pdf

Shuiwang Ji, Xinyi Xu, Cheng Deng, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Computational modeling of cellular structures using conditional deep generative networks

Zhengyang Wang, Hao Yuan, Shuiwang Ji, 2018, Bioinform..

iCapsNets: Towards Interpretable Capsule Networks for Text Classification pdf

Shuiwang Ji, Xia Hu, Zhengyang Wang, 2020, ArXiv.

Learning Convolutional Text Representations for Visual Question Answering

Zhengyang Wang, Shuiwang Ji, Shuiwang Ji, 2017, SDM.

Group Equivariant Fourier Neural Operators for Partial Differential Equations

Shuiwang Ji, Stephan Wojtowytsch, Xuan Zhang, 2023, ICML.

An Efficient Policy Gradient Method for Conditional Dialogue Generation

Shuiwang Ji, Lei Cai, Shuiwang Ji, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Extracting shared subspace for multi-label classification

Jieping Ye, Lei Tang, Shuiwang Ji, 2008, KDD.

Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli

Bian Wu, Shuiwang Ji, Lei Cai, 2018, Neuroinformatics.

Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

Yongjun Chen, Shuiwang Ji, Hongyang Gao, 2019, WWW.

Jieping Ye, Shuiwang Ji, Jieping Ye, 2008, IEEE Transactions on Knowledge and Data Engineering.

Discriminant sparse neighborhood preserving embedding for face recognition

Wei Jia, Zhenan Sun, Jie Gui, 2012, Pattern Recognit..

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality

Shuiwang Ji, Shaoting Zhang, Aidong Lu, 2018, Neuroinformatics.

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

Zhengyang Wang, Hao Yuan, Shuiwang Ji, 2017, SDM.

A least squares formulation for canonical correlation analysis

Jieping Ye, Liang Sun, Shuiwang Ji, 2008, ICML '08.

A least squares formulation for a class of generalized eigenvalue problems in machine learning

Jieping Ye, Liang Sun, Shuiwang Ji, 2009, ICML '09.

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, arXiv.org.

Detecting Human Actions in Surveillance Videos

Ming Yang, Yihong Gong, Thomas S. Huang, 2009, TRECVID.

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis

Andrey N. Chernikov, Shuiwang Ji, S. Newfeld, 2013, BMC Bioinformatics.

Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation pdf

Dinggang Shen, Zhengyang Wang, Shuiwang Ji, 2018, ArXiv.

Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples pdf

Shuiwang Ji, Lei Cai, Sudhir Kumar, 2020, IEEE Transactions on Neural Networks and Learning Systems.

A mesh generation and machine learning framework for Drosophilagene expression pattern image analysis

Andrey N. Chernikov, Daming Feng, Shuiwang Ji, 2013, BMC Bioinformatics.

Evolutionary Soft Co-Clustering

Rui Zhang, Shuiwang Ji, Wenlu Zhang, 2013, SDM.

Multi-Modality Disease Modeling via Collective Deep Matrix Factorization

Jiayu Zhou, Qi Wang, Shuiwang Ji, 2017, KDD.

DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning

Zhi-Hua Zhou, Jieping Ye, Shuiwang Ji, 2009, IJCAI.

Discriminant kernel and regularization parameter learning via semidefinite programming

Jieping Ye, Jianhui Chen, Shuiwang Ji, 2007, ICML '07.

Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning

Zhi-Hua Zhou, Jieping Ye, Shuiwang Ji, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Towards Symmetry-Aware Generation of Periodic Materials

Shuiwang Ji, Youzhi Luo, Chengkai Liu, 2023, ArXiv.

A Score-Based Model for Learning Neural Wavefunctions

Shuiwang Ji, Shenglong Xu, Xuan Zhang, 2023, ArXiv.

3D Molecular Geometry Analysis with 2D Graphs

Shuiwang Ji, Yaochen Xie, Maho Nakata, 2023, ArXiv.

MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery pdf

Shuiwang Ji, Zhao Xu, Lei Cai, 2020, ArXiv.

Graph U-Nets

Shuiwang Ji, Hongyang Gao, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Preprint Submitted to Ieee Transactions on Knowledge and Data Engineering 1 Multi-view Partitioning via Tensor Methods

B. Moor, Shuiwang Ji, W. Glänzel, 2022 .

A Mathematical View of Attention Models in Deep Learning

Shuiwang Ji, Yaochen Xie, 2020 .

Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction

Shuiwang Ji, Youzhi Luo, Yi Liu, 2023, ICML.

CleftNet: Augmented Deep Learning for Synaptic Cleft Detection From Brain Electron Microscopy pdf

Shuiwang Ji, Yi Liu, Shuiwang Ji, 2021, IEEE Transactions on Medical Imaging.

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery.

Tianbao Yang, Shuiwang Ji, Yaochen Xie, 2020, Bioinformatics.

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

Shuiwang Ji, Shurui Gui, Youzhi Luo, 2023, NeurIPS.

FlowX: Towards Explainable Graph Neural Networks via Message Flows

Shuiwang Ji, Hao Yuan, Shurui Gui, 2022, IEEE transactions on pattern analysis and machine intelligence.

Ieee Transactions on Pattern Analysis and Machine Intelligence 1 3d Convolutional Neural Networks for Human Action Recognition

Ming Yang, Kai Yu, Shuiwang Ji, 2022 .

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Shuiwang Ji, Haiyang Yu, Youzhi Luo, 2023, ArXiv.

A Latent Diffusion Model for Protein Structure Generation

Shuiwang Ji, Cong Fu, Kanji Uchino, 2023, LoG.

Spherical Message Passing for 3D Molecular Graphs

Shuiwang Ji, Bora Oztekin, Limei Wang, 2021, ICLR.

Dense Transformer Networks for Brain Electron Microscopy Image Segmentation

Yongjun Chen, Ian Davidson, Shuiwang Ji, 2019, IJCAI.

Multi-Task Feature Interaction Learning

Jiayu Zhou, Jianpeng Xu, Shuiwang Ji, 2016, KDD.

Graph and Geometry Generative Modeling for Drug Discovery

J. Leskovec, Shuiwang Ji, Wengong Jin, 2023, KDD.

Graph Neural Networks with Adaptive Frequency Response Filter

Shuiwang Ji, Kaize Ding, Jundong Li, 2021, ArXiv.

Non-Local U-Nets for Biomedical Image Segmentation

Shuiwang Ji, D. Shen, Zhengyang Wang, 2020, AAAI.

Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci

Shuiwang Ji, Tianming Liu, Xiaoping Hu, 2015, Brain Structure and Function.

Global analysis of gene expression and projection target correlations in the mouse brain

Shuiwang Ji, Hanchuan Peng, Tao Zeng, 2015, Brain Informatics.

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Connor W. Coley, Chaitanya K. Joshi, Aria Mansouri Tehrani, 2023, ArXiv.

JARVIS-Leaderboard: a large scale benchmark of materials design methods

Luke E. K. Achenie, Sterling G. Baird, Shuiwang Ji, 2023, npj Computational Materials.