Shuiwang Ji
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Computer Science
Why Is Shuiwang Ji Influential?
(Suggest an Edit or Addition)Shuiwang Ji's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- 3D Convolutional Neural Networks for Human Action Recognition (2010) (4792)
- Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization (2009) (706)
- Deep convolutional neural networks for multi-modality isointense infant brain image segmentation (2015) (684)
- Graph U-Nets (2019) (574)
- An accelerated gradient method for trace norm minimization (2009) (568)
- Large-Scale Learnable Graph Convolutional Networks (2018) (417)
- IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information (2020) (415)
- Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis (2014) (385)
- Towards Deeper Graph Neural Networks (2020) (293)
- Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis (2011) (288)
- Hypergraph spectral learning for multi-label classification (2008) (251)
- Discriminant sparse neighborhood preserving embedding for face recognition (2012) (250)
- Partial Least Squares (2016) (242)
- Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning (2010) (229)
- A Robust Deep Model for Improved Classification of AD/MCI Patients (2015) (217)
- Extracting shared subspace for multi-label classification (2008) (201)
- Explainability in Graph Neural Networks: A Taxonomic Survey (2020) (183)
- Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection (2008) (170)
- A shared-subspace learning framework for multi-label classification (2010) (168)
- XGNN: Towards Model-Level Explanations of Graph Neural Networks (2020) (161)
- Feature Selection Based on Structured Sparsity: A Comprehensive Study (2017) (160)
- Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis (2015) (156)
- On Explainability of Graph Neural Networks via Subgraph Explorations (2021) (129)
- Self-Supervised Learning of Graph Neural Networks: A Unified Review (2021) (119)
- Linear Dimensionality Reduction for Multi-label Classification (2009) (117)
- StructPool: Structured Graph Pooling via Conditional Random Fields (2020) (114)
- Smoothed dilated convolutions for improved dense prediction (2018) (106)
- Non-Local U-Nets for Biomedical Image Segmentation (2018) (104)
- Multi-class Discriminant Kernel Learning via Convex Programming (2008) (103)
- Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation (2017) (103)
- Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction (2017) (93)
- A least squares formulation for canonical correlation analysis (2008) (89)
- A machine learning approach for the identification of protein secondary structure elements from electron cryo-microscopy density maps. (2012) (89)
- On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares (2009) (80)
- XFake: Explainable Fake News Detector with Visualizations (2019) (72)
- Multiview Partitioning via Tensor Methods (2013) (72)
- Spherical Message Passing for 3D Graph Networks (2021) (71)
- DeepEM3D: approaching human‐level performance on 3D anisotropic EM image segmentation (2017) (71)
- GraphDF: A Discrete Flow Model for Molecular Graph Generation (2021) (70)
- Non-Local Graph Neural Networks (2020) (67)
- Adversarial Attacks and Defenses on Graphs (2020) (67)
- Deep Adversarial Learning for Multi-Modality Missing Data Completion (2018) (65)
- Mining discrete patterns via binary matrix factorization (2009) (64)
- Multi-label Multiple Kernel Learning (2008) (63)
- A deep transfer learning approach for improved post-traumatic stress disorder diagnosis (2017) (60)
- Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning (2009) (59)
- Line Graph Neural Networks for Link Prediction (2020) (57)
- Deep convolutional neural networks for annotating gene expression patterns in the mouse brain (2015) (56)
- DIG: A Turnkey Library for Diving into Graph Deep Learning Research (2021) (54)
- FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis (2011) (54)
- Deep models for brain EM image segmentation: novel insights and improved performance (2016) (52)
- Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising (2020) (51)
- ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions (2018) (48)
- Discriminant Analysis for Dimensionality Reduction: An Overview of Recent Developments (2010) (47)
- A bag-of-words approach for Drosophila gene expression pattern annotation (2009) (47)
- Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy (2016) (45)
- Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery. (2020) (45)
- Robust Deep Learning for Improved Classification of AD/MCI Patients (2014) (45)
- Deep Convolutional Neural Networks for Multi-instance Multi-task Learning (2015) (43)
- Pixel Transposed Convolutional Networks (2020) (43)
- A Multi-Scale Approach for Graph Link Prediction (2020) (43)
- Detecting Human Actions in Surveillance Videos (2009) (42)
- Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation (2017) (41)
- Second-Order Pooling for Graph Neural Networks (2020) (41)
- Integrative analysis of the connectivity and gene expression atlases in the mouse brain (2014) (41)
- ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs (2021) (40)
- Pixel Deconvolutional Networks (2017) (40)
- Graph Representation Learning via Hard and Channel-Wise Attention Networks (2019) (39)
- A least squares formulation for a class of generalized eigenvalue problems in machine learning (2009) (39)
- Automated annotation of Drosophila gene expression patterns using a controlled vocabulary (2008) (38)
- Topology-Aware Graph Pooling Networks (2020) (38)
- Drosophila gene expression pattern annotation using sparse features and term-term interactions (2009) (37)
- How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and its Kernel Version? (2014) (36)
- On Attribution of Recurrent Neural Network Predictions via Additive Decomposition (2019) (35)
- A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection (2019) (34)
- Drosophila gene expression pattern annotation through multi-instance multi-label learning. (2012) (34)
- GraphEBM: Molecular Graph Generation with Energy-Based Models (2021) (33)
- Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods (2019) (33)
- Deep Learning of High-Order Interactions for Protein Interface Prediction (2020) (33)
- Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering (2013) (31)
- High-resolution prediction of mouse brain connectivity using gene expression patterns. (2015) (29)
- Discriminant kernel and regularization parameter learning via semidefinite programming (2007) (29)
- Multi-Task Feature Interaction Learning (2016) (28)
- AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter (2021) (27)
- Multi-View Missing Data Completion (2018) (27)
- Multi-Modality Disease Modeling via Collective Deep Matrix Factorization (2017) (27)
- Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci (2015) (25)
- Global Pixel Transformers for Virtual Staining of Microscopy Images (2019) (24)
- Structural Graphical Lasso for Learning Mouse Brain Connectivity (2015) (24)
- Generating 3D Molecules for Target Protein Binding (2022) (23)
- Kronecker Attention Networks (2020) (22)
- Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming (2007) (22)
- Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations (2019) (21)
- Computational modeling of cellular structures using conditional deep generative networks (2018) (21)
- Demographic Prediction of Mobile User from Phone Usage (2012) (21)
- Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval (2012) (20)
- Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence (2021) (20)
- Learning subspace kernels for classification (2008) (19)
- Segmenting delaminations in carbon fiber reinforced polymer composite CT using convolutional neural networks (2016) (18)
- An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch (2022) (18)
- A sparsity-inducing formulation for evolutionary co-clustering (2012) (18)
- Computational network analysis of the anatomical and genetic organizations in the mouse brain (2011) (17)
- Evolutionary soft co-clustering: formulations, algorithms, and applications (2015) (17)
- Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study (2008) (17)
- CorDEL: A Contrastive Deep Learning Approach for Entity Linkage (2020) (16)
- Dense Transformer Networks (2017) (16)
- Global voxel transformer networks for augmented microscopy (2020) (15)
- Interpreting Image Classifiers by Generating Discrete Masks (2020) (14)
- Machine Learning Explanations to Prevent Overtrust in Fake News Detection (2020) (14)
- ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs (2022) (14)
- Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression (2013) (14)
- Adaptive diffusion kernel learning from biological networks for protein function prediction (2008) (13)
- Image-level and group-level models for Drosophila gene expression pattern annotation (2013) (13)
- Sparsity Learning Formulations for Mining Time-Varying Data (2015) (12)
- A unified framework for generalized Linear Discriminant Analysis (2008) (12)
- Voxel Deconvolutional Networks for 3D Brain Image Labeling (2018) (12)
- Global analysis of gene expression and projection target correlations in the mouse brain (2015) (12)
- Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns (2014) (11)
- A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis (2013) (11)
- Collaborative Multi-View Denoising (2016) (10)
- Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction (2019) (10)
- A Probabilistic Latent Semantic Analysis Model for Coclustering the Mouse Brain Atlas (2013) (10)
- Efficient and Invariant Convolutional Neural Networks for Dense Prediction (2017) (9)
- Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs (2021) (9)
- Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality (2018) (9)
- Learning Convolutional Text Representations for Visual Question Answering (2017) (9)
- Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli (2018) (8)
- Automated Data Augmentations for Graph Classification (2022) (8)
- GraphFM: Improving Large-Scale GNN Training via Feature Momentum (2022) (8)
- Multi-Label Dimensionality Reduction (Chapman & Hall/CRC Machine Learning & Pattern Recognition) (2011) (8)
- Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation (2018) (8)
- GOOD: A Graph Out-of-Distribution Benchmark (2022) (8)
- DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding (2022) (8)
- Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence (2021) (7)
- Periodic Graph Transformers for Crystal Material Property Prediction (2022) (7)
- CleftNet: Augmented Deep Learning for Synaptic Cleft Detection From Brain Electron Microscopy (2021) (7)
- Learning Local and Global Multi-context Representations for Document Classification (2019) (6)
- Learning Protein Representations via Complete 3D Graph Networks (2022) (6)
- Adaptive Convolutional ReLUs (2020) (6)
- Parallel Lasso Screening for Big Data Optimization (2016) (6)
- Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction (2017) (5)
- MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery (2020) (5)
- Trust Evolution Over Time in Explainable AI for Fake News Detection (2020) (5)
- Evolutionary Soft Co-Clustering (2013) (5)
- Task-Agnostic Graph Explanations (2022) (5)
- Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks (2021) (5)
- iCapsNets: Towards Interpretable Capsule Networks for Text Classification (2020) (4)
- Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions (2017) (4)
- Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions (2022) (4)
- Dense Transformer Networks for Brain Electron Microscopy Image Segmentation (2019) (4)
- Node2Seq: Towards Trainable Convolutions in Graph Neural Networks (2021) (4)
- Automated Gene Expression Pattern Annotation in the Mouse Brain (2014) (3)
- Adversarial Graph Disentanglement (2021) (3)
- BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology (2022) (3)
- Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping (2020) (3)
- Self-Supervised Representation Learning via Latent Graph Prediction (2022) (3)
- Deep Neural Networks with Knowledge Instillation (2020) (3)
- Development of Xanthene‐Based Fluorescent Dyes: Machine Learning‐Assisted Prediction vs. TD‐DFT Prediction and Experimental Validation (2021) (3)
- A new perspective on building efficient and expressive 3D equivariant graph neural networks (2023) (3)
- Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks (2022) (2)
- Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis (2020) (2)
- Collaborative MultiView Denoising (2016) (2)
- Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences (2022) (2)
- A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis (2021) (2)
- Augmented Equivariant Attention Networks for Electron Microscopy Image Super-Resolution (2020) (2)
- Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems (2022) (2)
- Learning Hierarchical Protein Representations via Complete 3D Graph Networks (2022) (2)
- Three-dimensional protein shape similarity analysis based on hybrid features. (2018) (2)
- A Mathematical View of Attention Models in Deep Learning (2020) (2)
- Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings (2022) (1)
- Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval (2012) (1)
- Group Contrastive Self-Supervised Learning on Graphs (2021) (1)
- Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering (2013) (1)
- Deep convolutional neural networks for annotating gene expression patterns in the mouse brain (2015) (1)
- zhengyang-wang/GVTNets: Code for "Global Voxel Transformer Networks for Augmented Microscopy" (2020) (1)
- Principal Component Analysis and Autoencoders (2020) (1)
- Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models (2022) (1)
- An Interpretable Neural Model with Interactive Stepwise Influence (2019) (1)
- A mesh generation and machine learning framework for Drosophilagene expression pattern image analysis (2013) (1)
- FlowX: Towards Explainable Graph Neural Networks via Message Flows (2022) (1)
- Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images (2019) (1)
- Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality (2018) (1)
- Back-Propagation: From Fully Connected to Convolutional Layers (2019) (0)
- Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples (2020) (0)
- Periodic Subsampling Shared Standard Convolution Reinterlacing Dilated Convolution (2019) (0)
- Joint Dimensionality Reduction and Classification (2016) (0)
- An Efficient Policy Gradient Method for Conditional Dialogue Generation (2019) (0)
- Towards Structured NLP Interpretation via Graph Explainers † (2021) (0)
- A Neural Network View of Kernel Methods (2020) (0)
- Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence (2021) (0)
- Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution (2023) (0)
- Topology-Aware Pooling via Graph Attention (2019) (0)
- IDM 2017: Workshop on Interpretable Data Mining -- Bridging the Gap between Shallow and Deep Models (2017) (0)
- Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli (2018) (0)
- Sparsity Learning Formulations for Mining (2015) (0)
- Provably Convergent Subgraph-wise Sampling for Fast GNN Training (2023) (0)
- BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets. (2023) (0)
- Computational analysis of drosophila gene expression pattern images (2010) (0)
- Evolutionary soft co-clustering: formulations, algorithms, and applications (2014) (0)
- Allen mouse brain atlases reveal different neural connection and gene expression patterns in cerebellum gyri and sulci (2014) (0)
- Augmented Equivariant Attention Networks for Microscopy Image Transformation (2020) (0)
- Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities (2021) (0)
- Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns (2014) (0)
- Global analysis of gene expression and projection target correlations in the mouse brain (2015) (0)
- Image-level and group-level models for Drosophilagene expression pattern annotation (2013) (0)
- Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification (2022) (0)
- Logistic Regression: From Binary to Multi-Class (2020) (0)
- A N A UTOREGRESSIVE F LOW M ODEL FOR 3D M OLEC ULAR G EOMETRY G ENERATION FROM S CRATCH (2022) (0)
- Extracting Shared Subspaces for Multi-label Classificatio n (2008) (0)
- Frontiers of Graph Neural Networks with DIG (2022) (0)
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