Split LBI: An Iterative Regularization Path with Structural Sparsity. - Chendi Huang; Xinwei Sun 001; Jiechao Xiong; Yuan Yao 011 (NIPS, 2016)

GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction. - Xinwei Sun 001; Lingjing Hu; Yuan Yao 011; Yizhou Wang 001 (MICCAI (3), 2017)

Zero-shot Learning via Shared-Reconstruction-Graph Pursuit. - Bo Zhao 015; Xinwei Sun 001; Yuan Yao 011; Yizhou Wang 001 (CoRR, 2017)

MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning. - Bo Zhao 015; Xinwei Sun 001; Yanwei Fu 001; Yuan Yao 011; Yizhou Wang 001 (ICML, 2018)

FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis. - Xinwei Sun 001; Lingjing Hu; Fandong Zhang; Yuan Yao 011; Yizhou Wang 001 (MICCAI (1), 2018)

A Margin-based MLE for Crowdsourced Partial Ranking. - Qianqian Xu; Jiechao Xiong; Xinwei Sun 001; Zhiyong Yang 001; Xiaochun Cao; Qingming Huang; Yuan Yao 011 (ACM Multimedia, 2018)

Cascaded Generative and Discriminative Learning for Microcalcification Detection in Breast Mammograms. - Fandong Zhang; Ling Luo; Xinwei Sun 001; Zhen Zhou; Xiuli Li; Yizhou Yu; Yizhou Wang 001 (CVPR, 2019)

Learning With Unsure Data for Medical Image Diagnosis. - Botong Wu; Xinwei Sun 001; Lingjing Hu; Yizhou Wang 001 (ICCV, 2019)

iSplit LBI: Individualized Partial Ranking with Ties via Split LBI. - Qianqian Xu; Xinwei Sun 001; Zhiyong Yang 001; Xiaochun Cao; Qingming Huang; Yuan Yao 011 (NeurIPS, 2019)

Zero-Shot Learning Via Recurrent Knowledge Transfer. - Bo Zhao 015; Xinwei Sun 001; Xiaopeng Hong; Yuan Yao 011; Yizhou Wang 001 (WACV, 2019)

S2-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning. - Yanwei Fu 001; Donghao Li; Xinwei Sun 001; Shun Zhang; Yizhou Wang 001; Yuan Yao 011 (CoRR, 2019)

Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence. - Yanwei Fu 001; Chen Liu 030; Donghao Li; Xinwei Sun 001; Jinshan Zeng; Yuan Yao 011 (CoRR, 2019)

TCGM: An Information-Theoretic Framework for Semi-supervised Multi-modality Learning. - Xinwei Sun 001; Yilun Xu; Peng Cao 004; Yuqing Kong; Lingjing Hu; Shanghang Zhang; Yizhou Wang 001 (ECCV (3), 2020)

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths. - Yanwei Fu 001; Chen Liu 030; Donghao Li; Xinwei Sun 001; Jinshan Zeng; Yuan Yao 011 (ICML, 2020)

Leveraging both Lesion Features and Procedural Bias in Neuroimaging: An Dual-Task Split dynamics of inverse scale space. - Xinwei Sun 001; Wenjing Han; Lingjing Hu; Yuan Yao 011; Yizhou Wang 001 (CoRR, 2020)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2020)

Latent Causal Invariant Model. - Xinwei Sun 001; Botong Wu; Chang Liu 030; Xiangyu Zheng; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (CoRR, 2020)

Identifying Invariant Texture Violation for Robust Deepfake Detection. - Xinwei Sun 001; Botong Wu; Wei Chen 034 (CoRR, 2020)

Disease Forecast via Progression Learning. - Botong Wu; Sijie Ren; Jing Li 091; Xinwei Sun 001; Shiming Li; Yizhou Wang 001 (CoRR, 2020)

Perturbed Amplitude Flow for Phase Retrieval. - Bing Gao; Xinwei Sun 001; Yang Wang 020; Zhiqiang Xu 001 (IEEE Trans. Signal Process., 2020)

Causal Hidden Markov Model for Time Series Disease Forecasting. - Jing Li 091; Botong Wu; Xinwei Sun 001; Yizhou Wang 001 (CVPR, 2021)

Forecasting Irreversible Disease via Progression Learning. - Botong Wu; Sijie Ren; Jing Li 091; Xinwei Sun 001; Shiming Li; Yizhou Wang 001 (CVPR, 2021)

CA-Net: Leveraging Contextual Features for Lung Cancer Prediction. - Mingzhou Liu 001; Fandong Zhang; Xinwei Sun 001; Yizhou Yu; Yizhou Wang 001 (MICCAI (5), 2021)

DAE-GCN: Identifying Disease-Related Features for Disease Prediction. - Chu-ran Wang; Xinwei Sun 001; Fandong Zhang; Yizhou Yu; Yizhou Wang 001 (MICCAI (5), 2021)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Haoyue Tang; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

Recovering Latent Causal Factor for Generalization to Distributional Shifts. - Xinwei Sun 001; Botong Wu; Xiangyu Zheng; Chang Liu 030; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

Causally Invariant Predictor with Shift-Robustness. - Xiangyu Zheng; Xinwei Sun 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition. - Mingzhou Liu 001; Xinwei Sun 001; Fandong Zhang; Yizhou Yu; Yizhou Wang 001 (CoRR, 2021)

Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification. - Chu-ran Wang; Jing Li 091; Fandong Zhang; Xinwei Sun 001; Hao Dong 003; Yizhou Yu; Yizhou Wang 001 (IEEE Trans. Image Process., 2021)

Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels. - Yikai Wang 002; Xinwei Sun 001; Yanwei Fu 001 (CVPR, 2022)

Domain Invariant Model with Graph Convolutional Network for Mammogram Classification. - Chu-ran Wang; Jing Li 091; Xinwei Sun 001; Fandong Zhang; Yizhou Yu; Yizhou Wang 001 (CoRR, 2022)

Sparse Learning in AI: A Differential Inclusion Perspective. - Xinwei Sun 001 (ACM TUR-C, 2023)

A New Causal Decomposition Paradigm towards Health Equity. - Xinwei Sun 001; Xiangyu Zheng; Jim Weinstein (AISTATS, 2023)

Out-of-distribution Representation Learning for Time Series Classification. - Wang Lu; Jindong Wang 001; Xinwei Sun 001; Yiqiang Chen 001; Xing Xie 001 (ICLR, 2023)

Learning Domain-Agnostic Representation for Disease Diagnosis. - Chu-ran Wang; Jing Li 091; Xinwei Sun 001; Fandong Zhang; Yizhou Yu; Yizhou Wang 001 (ICLR, 2023)

Which Invariance Should We Transfer? A Causal Minimax Learning Approach. - Mingzhou Liu 001; Xiangyu Zheng; Xinwei Sun 001; Fang Fang 003; Yizhou Wang 001 (ICML, 2023)

Causal Discovery from Subsampled Time Series with Proxy Variables. - Mingzhou Liu 001; Xinwei Sun 001; Lingjing Hu; Yizhou Wang 001 (NeurIPS, 2023)

Causal Discovery with Unobserved Variables: A Proxy Variable Approach. - Mingzhou Liu 001; Xinwei Sun 001; Yu Qiao 001; Yizhou Wang 001 (CoRR, 2023)

Exploring Counterfactual Alignment Loss towards Human-centered AI. - Mingzhou Liu 001; Xinwei Sun 001; Ching-Wen Lee; Yu Qiao 001; Yizhou Wang 001 (CoRR, 2023)

Exploring Structural Sparsity of Deep Networks Via Inverse Scale Spaces. - Yanwei Fu 001; Chen Liu 030; Donghao Li; Zuyuan Zhong; Xinwei Sun 001; Jinshan Zeng; Yuan Yao 011 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

PatchMix Augmentation to Identify Causal Features in Few-Shot Learning. - Chengming Xu 001; Chen Liu 030; Xinwei Sun 001; Siqian Yang; Yabiao Wang; Chengjie Wang; Yanwei Fu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Doubly Robust Proximal Causal Learning for Continuous Treatments. - Yong Wu; Yanwei Fu 001; Shouyan Wang; Xinwei Sun 001 (ICLR, 2024)

Causal Discovery via Conditional Independence Testing with Proxy Variables. - Mingzhou Liu 001; Xinwei Sun 001; Yu Qiao 001; Yizhou Wang 001 (ICML, 2024)

LAC-Net: Linear-Fusion Attention-Guided Convolutional Network for Accurate Robotic Grasping Under the Occlusion. - Jinyu Zhang; Yongchong Gu; Jianxiong Gao; Haitao Lin; Qiang Sun 008; Xinwei Sun 001; Xiangyang Xue 001; Yanwei Fu 001 (IROS, 2024)

Exploring High-dimensional Search Space via Voronoi Graph Traversing. - Aidong Zhao; Xuyang Zhao; Tianchen Gu; Zhaori Bi; Xinwei Sun 001; Changhao Yan; Fan Yang 001; Dian Zhou; Xuan Zeng 001 (UAI, 2024)

Bayesian Intervention Optimization for Causal Discovery. - Yuxuan Wang 005; Mingzhou Liu 001; Xinwei Sun 001; Wei Wang 115; Yizhou Wang 001 (CoRR, 2024)

Robust Network Learning via Inverse Scale Variational Sparsification. - Zhiling Zhou; Zirui Liu 012; Chengming Xu 001; Yanwei Fu 001; Xinwei Sun 001 (CoRR, 2024)

LEA: Learning Latent Embedding Alignment Model for fMRI Decoding and Encoding. - Xuelin Qian; Yikai Wang 002; Xinwei Sun 001; Yanwei Fu 001; Xiangyang Xue 001; Jianfeng Feng (Trans. Mach. Learn. Res., 2024)

Knockoffs-SPR: Clean Sample Selection in Learning With Noisy Labels. - Yikai Wang 002; Yanwei Fu 001; Xinwei Sun 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Diversify: A General Framework for Time Series Out-of-Distribution Detection and Generalization. - Wang Lu; Jindong Wang 001; Xinwei Sun 001; Yiqiang Chen 001; Xiangyang Ji; Qiang Yang 001; Xing Xie 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging Analysis. - Wenjing Han; Yueming Wu 005; Xinwei Sun 001; Lingjing Hu; Yizhou Wang 001 (AISTATS, 2025)

Learning Causal Alignment for Reliable Disease Diagnosis. - Mingzhou Liu 001; Ching-Wen Lee; Xinwei Sun 001; Xueqing Yu; Yu Qiao 001; Yizhou Wang 001 (ICLR, 2025)

Adaptive Pruning of Pretrained Transformer via Differential Inclusions. - Yizhuo Ding; Ke Fan; Yikai Wang 002; Xinwei Sun 001; Yanwei Fu 001 (ICLR, 2025)

A new formulation of Lipschitz constrained with functional gradient learning for GANs. - Chang Wan; Ke Fan; Xinwei Sun 001; Yanwei Fu 001; Minglu Li 001; Yunliang Jiang; Zhonglong Zheng (Mach. Learn., 2025)

Revisiting Large Language Model Pruning using Neuron Semantic Attribution. - Yizhuo Ding; Xinwei Sun 001; Yanwei Fu 001; Guosheng Hu (CoRR, 2025)

Conditional Local Independence Testing for Dynamic Causal Discovery. - Mingzhou Liu 001; Xinwei Sun 001; Yizhou Wang 001 (CoRR, 2025)