Feature Selection Algorithm Based on Association Rules Mining Method. - Jianwen Xie; Jianhua Wu; Qingquan Qian (ACIS-ICIS, 2009)

A particle swarm optimization algorithm with crossover for vehicle routing problem with time windows. - Weigang Jiang; Yuanbiao Zhang; Jianwen Xie (CISched, 2009)

Feature Subset Selection Using Association Rules. - Jianwen Xie; Weigang Jiang; Xiaoxiang Liu (IC-AI, 2009)

Linear Programming With Fuzzy Relation Constraints: A Molecular-Diffusion Based Particle Swarm Optimization Approach. - Jianwen Xie; Xiaoxiang Liu; Weigang Jiang (IC-AI, 2009)

Vehicle Routing Problem with Time Windows: A Hybrid Particle Swarm Optimization Approach. - Xiaoxiang Liu; Weigang Jiang; Jianwen Xie (ICNC (4), 2009)

A Particle Swarm Optimization Algorithm with Crossover for Resource Constrained Project Scheduling Problem. - Ming Li; Yuanbiao Zhang; Weigang Jiang; Jianwen Xie (SSME, 2009)

Learning Inhomogeneous FRAME Models for Object Patterns. - Jianwen Xie; Wenze Hu; Song-Chun Zhu; Ying Nian Wu (CVPR, 2014)

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD. - Ariana E. Anderson; Pamela K. Douglas; Wesley T. Kerr; Virginia S. Haynes; Alan L. Yuille; Jianwen Xie; Ying Nian Wu; Jesse A. Brown; Mark S. Cohen (NeuroImage, 2014)

Learning Sparse FRAME Models for Natural Image Patterns. - Jianwen Xie; Wenze Hu; Song-Chun Zhu; Ying Nian Wu (Int. J. Comput. Vis., 2015)

A Theory of Generative ConvNet. - Jianwen Xie; Yang Lu 006; Song-Chun Zhu; Ying Nian Wu (ICML, 2016)

Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms. - Jianwen Xie; Pamela K. Douglas; Ying Nian Wu; Arthur L. Brody; Ariana E. Anderson (CoRR, 2016)

Cooperative Training of Descriptor and Generator Networks. - Jianwen Xie; Yang Lu 006; Song-Chun Zhu; Ying Nian Wu (CoRR, 2016)

Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet. - Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (CoRR, 2016)

Generative Modeling and Unsupervised Learning in Computer Vision. - Jianwen Xie (2016)

Generative Hierarchical Learning of Sparse FRAME Models. - Jianwen Xie; Yifei Xu; Erik Nijkamp; Ying Nian Wu; Song-Chun Zhu (CVPR, 2017)

Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet. - Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (CVPR, 2017)

Super-Trajectory for Video Segmentation. - Wenguan Wang; Jianbing Shen; Jianwen Xie; Fatih Porikli (ICCV, 2017)

Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching. - Jianwen Xie; Yang Lu 006; Ruiqi Gao; Ying Nian Wu (AAAI, 2018)

Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer. - Haoshu Fang; Guansong Lu; Xiaolin Fang 002; Jianwen Xie; Yu-Wing Tai; Cewu Lu (CVPR, 2018)

Learning Descriptor Networks for 3D Shape Synthesis and Analysis. - Jianwen Xie; Zilong Zheng; Ruiqi Gao; Wenguan Wang; Song-Chun Zhu; Ying Nian Wu (CVPR, 2018)

A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects. - Yuanlu Xu; Lei Qin; Xiaobai Liu; Jianwen Xie; Song-Chun Zhu (CVPR, 2018)

Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion. - Ruiqi Gao; Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (CoRR, 2018)

Learning Dynamic Generator Model by Alternating Back-Propagation through Time. - Jianwen Xie; Ruiqi Gao; Zilong Zheng; Song-Chun Zhu; Ying Nian Wu (AAAI, 2019)

Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection. - Yunlu Xu; Chengwei Zhang 003; Zhanzhan Cheng; Jianwen Xie; Yi Niu; Shiliang Pu; Fei Wu 001 (AAAI, 2019)

Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning. - Yizhe Zhu; Jianwen Xie; Bingchen Liu; Ahmed Elgammal (ICCV, 2019)

Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion. - Ruiqi Gao; Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (ICLR (Poster), 2019)

Semantic-Guided Multi-Attention Localization for Zero-Shot Learning. - Yizhe Zhu; Jianwen Xie; Zhiqiang Tang 001; Xi Peng 005; Ahmed Elgammal (NeurIPS, 2019)

Multimodal Conditional Learning with Fast Thinking Policy-like Model and Slow Thinking Planner-like Model. - Jianwen Xie; Zilong Zheng; Xiaolin Fang 002; Song-Chun Zhu; Ying Nian Wu (CoRR, 2019)

Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1. - Ruiqi Gao; Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (CoRR, 2019)

Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning. - Yizhe Zhu; Jianwen Xie; Zhiqiang Tang 001; Xi Peng 005; Ahmed Elgammal (CoRR, 2019)

Efficient Video Scene Text Spotting: Unifying Detection, Tracking, and Recognition. - Zhanzhan Cheng; Jing Lu 004; Jianwen Xie; Yi Niu; Shiliang Pu; Fei Wu 001 (CoRR, 2019)

Learning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning. - Yizhe Zhu; Jianwen Xie; Bingchen Liu; Ahmed Elgammal (CoRR, 2019)

Representation Learning: A Statistical Perspective. - Jianwen Xie; Ruiqi Gao; Erik Nijkamp; Song-Chun Zhu; Ying Nian Wu (CoRR, 2019)

Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. - Jianwen Xie; Ruiqi Gao; Zilong Zheng; Song-Chun Zhu; Ying Nian Wu (AAAI, 2020)

Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection. - Jing Zhang 052; Jianwen Xie; Nick Barnes (ECCV (17), 2020)

Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. - Jianwen Xie; Yifei Xu; Zilong Zheng; Song-Chun Zhu; Ying Nian Wu (CoRR, 2020)

A Representational Model of Grid Cells Based on Matrix Lie Algebras. - Ruiqi Gao; Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (CoRR, 2020)

Cooperative Training of Descriptor and Generator Networks. - Jianwen Xie; Yang Lu 006; Ruiqi Gao; Song-Chun Zhu; Ying Nian Wu (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. - Jianwen Xie; Zilong Zheng; Xiaolin Fang 002; Song-Chun Zhu; Ying Nian Wu (AAAI, 2021)

Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler. - Jianwen Xie; Zilong Zheng; Ping Li 001 (AAAI, 2021)

MixBERT for Image-Ad Relevance Scoring in Advertising. - Tan Yu; Xiaokang Li; Jianwen Xie; Ruiyang Yin; Qing Xu; Ping Li 001 (CIKM, 2021)

Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction. - Dongsheng An; Jianwen Xie; Ping Li 001 (CVPR, 2021)

Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. - Jianwen Xie; Yifei Xu; Zilong Zheng; Song-Chun Zhu; Ying Nian Wu (CVPR, 2021)

Semi-Supervised Video Deraining With Dynamical Rain Generator. - Zongsheng Yue; Jianwen Xie; Qian Zhao 002; Deyu Meng (CVPR, 2021)

Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning. - Zilong Zheng; Jianwen Xie; Ping Li 001 (CVPR, 2021)

Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling. - Yang Zhao; Jianwen Xie; Ping Li 001 (ICLR, 2021)

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. - Ruiqi Gao; Jianwen Xie; Xue-Xin Wei; Song-Chun Zhu; Ying Nian Wu (NeurIPS, 2021)

Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction. - Jing Zhang 052; Jianwen Xie; Nick Barnes; Ping Li 001 (NeurIPS, 2021)

Unsupervised Single Image Super-resolution Under Complex Noise. - Zongsheng Yue; Qian Zhao 002; Jianwen Xie; Lei Zhang 006; Deyu Meng (CoRR, 2021)

Revisiting Video Saliency Prediction in the Deep Learning Era. - Wenguan Wang; Jianbing Shen; Jianwen Xie; Ming-Ming Cheng; Haibin Ling; Ali Borji (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns. - Jianwen Xie; Song-Chun Zhu; Ying Nian Wu (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion. - Ruiqi Gao; Jianwen Xie; Siyuan Huang 001; Yufan Ren; Song-Chun Zhu; Ying Nian Wu (AAAI, 2022)

Energy-Based Generative Cooperative Saliency Prediction. - Jing Zhang 052; Jianwen Xie; Zilong Zheng; Nick Barnes (AAAI, 2022)

Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel. - Zongsheng Yue; Qian Zhao 002; Jianwen Xie; Lei Zhang 006; Deyu Meng; Kwan-Yee K. Wong (CVPR, 2022)

A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model. - Jianwen Xie; Yaxuan Zhu; Jun Li 098; Ping Li 001 (ICLR, 2022)

CoopHash: Cooperative Learning of Multipurpose Descriptor and Contrastive Pair Generator via Variational MCMC Teaching for Supervised Image Hashing. - Khoa D. Doan; Jianwen Xie; Yaxuan Zhu; Yang Zhao; Ping Li 001 (CoRR, 2022)

Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning. - Jianwen Xie; Zilong Zheng; Xiaolin Fang 002; Song-Chun Zhu; Ying Nian Wu (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. - Jianwen Xie; Zilong Zheng; Ruiqi Gao; Wenguan Wang; Song-Chun Zhu; Ying Nian Wu (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Monocular 3D Pose Estimation via Pose Grammar and Data Augmentation. - Yuanlu Xu; Wenguan Wang; Tengyu Liu; Xiaobai Liu; Jianwen Xie; Song-Chun Zhu (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-Run Langevin Flow for Approximate Inference. - Jianwen Xie; Yaxuan Zhu; Yifei Xu; Dingcheng Li; Ping Li 001 (AAAI, 2023)

CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning. - Yang Zhao; Jianwen Xie; Ping Li 001 (AAAI, 2023)

Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation. - Yaxuan Zhu; Jianwen Xie; Ping Li 001 (AISTATS, 2023)

Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation. - Weinan Song; Yaxuan Zhu; Lei He 001; Yingnian Wu; Jianwen Xie (CoRR, 2023)

Molecule Design by Latent Prompt Transformer. - Deqian Kong; Yuhao Huang; Jianwen Xie; Ying Nian Wu (CoRR, 2023)

STANLEY: Stochastic Gradient Anisotropic Langevin Dynamics for Learning Energy-Based Models. - Belhal Karimi; Jianwen Xie; Ping Li 001 (CoRR, 2023)

An Energy-Based Prior for Generative Saliency. - Jing Zhang 052; Jianwen Xie; Nick Barnes; Ping Li 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Energy-Based Continuous Inverse Optimal Control. - Yifei Xu; Jianwen Xie; Tianyang Zhao; Chris L. Baker; Yibiao Zhao; Ying Nian Wu (IEEE Trans. Neural Networks Learn. Syst., 2023)

Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. - Yaxuan Zhu; Jianwen Xie; Ying Nian Wu; Ruiqi Gao (ICLR, 2024)

Molecule Design by Latent Prompt Transformer. - Deqian Kong; Yuhao Huang; Jianwen Xie; Edouardo Honig; Ming Xu; Shuanghong Xue; Pei Lin; Sanping Zhou; Sheng Zhong; Nanning Zheng 001; Ying Nian Wu (NeurIPS, 2024)

Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference. - Deqian Kong; Dehong Xu; Minglu Zhao; Bo Pang 004; Jianwen Xie; Andrew Lizarraga; Yuhao Huang; Sirui Xie; Ying Nian Wu (NeurIPS, 2024)

Latent Plan Transformer: Planning as Latent Variable Inference. - Deqian Kong; Dehong Xu; Minglu Zhao; Bo Pang 004; Jianwen Xie; Andrew Lizarraga; Yuhao Huang; Sirui Xie; Ying Nian Wu (CoRR, 2024)

Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer. - Deqian Kong; Yuhao Huang; Jianwen Xie; Edouardo Honig; Ming Xu; Shuanghong Xue; Pei Lin; Sanping Zhou; Sheng Zhong; Nanning Zheng 001; Ying Nian Wu (CoRR, 2024)

Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. - Peiyu Yu; Dinghuai Zhang; Hengzhi He; Xiaojian Ma 001; Ruiyao Miao; Yifan Lu; Yasi Zhang; Deqian Kong; Ruiqi Gao; Jianwen Xie; Guang Cheng 003; Ying Nian Wu (CoRR, 2024)

Super-Resolution Reconstruction of Infrared Images With Edge-Enhanced and Variable Activation Network. - Lei Hu 009; Jianwen Xie; Jiachen Ruan; Yunhong Li; Yongmei Zhang (IEEE Trans. Instrum. Meas., 2025)

Latent Space Energy-based Neural ODEs. - Sheng Cheng; Deqian Kong; Jianwen Xie; Kookjin Lee; Ying Nian Wu; Yezhou Yang (Trans. Mach. Learn. Res., 2025)

Scalable Language Models with Posterior Inference of Latent Thought Vectors. - Deqian Kong; Minglu Zhao; Dehong Xu; Bo Pang 004; Shu Wang 002; Edouardo Honig; Zhangzhang Si; Chuan Li; Jianwen Xie; Sirui Xie; Ying Nian Wu (CoRR, 2025)

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures. - Keqiang Yan; Montgomery Bohde; Andrii Kryvenko; Ziyu Xiang; Kaiji Zhao; Siya Zhu; Saagar Kolachina; Doguhan Saritürk; Jianwen Xie; Raymundo Arróyave; Xiaoning Qian; Xiaofeng Qian; et al. (CoRR, 2025)

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark. - Enxin Song; Wenhao Chai; Weili Xu; Jianwen Xie; Yuxuan Liu; Gaoang Wang (CoRR, 2025)

SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning. - Wufei Ma; Yu-Cheng Chou; Qihao Liu; Xingrui Wang; Celso de Melo; Jieneng Chen; Jianwen Xie; Alan L. Yuille (CoRR, 2025)

Latent Adaptive Planner for Dynamic Manipulation. - Donghun Noh; Deqian Kong; Minglu Zhao; Andrew Lizarraga; Jianwen Xie; Ying Nian Wu; Dennis W. Hong (CoRR, 2025)

DEL-ToM: Inference-Time Scaling for Theory-of-Mind Reasoning via Dynamic Epistemic Logic. - Yuheng Wu; Jianwen Xie; Denghui Zhang; Zhaozhuo Xu (CoRR, 2025)

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity. - Yide Ran; Wentao Guo; Jingwei Sun 002; Yanzhou Pan; Xiaodong Yu; Hao Wang; Jianwen Xie; Yiran Chen 001; Denghui Zhang; Zhaozhuo Xu (CoRR, 2025)

Natural Language Guided Ligand-Binding Protein Design. - Zhenqiao Song; Ramith Hettiarachchi; Chuan Li; Jianwen Xie; Lei Li (CoRR, 2025)

OAT-Rephrase: Optimization-Aware Training Data Rephrasing for Zeroth-Order LLM Fine-Tuning. - Jikai Long; Zijian Hu; Xiaodong Yu; Jianwen Xie; Zhaozhuo Xu (CoRR, 2025)

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials. - Cong Fu 003; Yuchao Lin; Zachary Krueger; Haiyang Yu 005; Maho Nakata; Jianwen Xie; Emine Küçükbenli; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations. - Yuchao Lin; Cong Fu 003; Zachary Krueger; Haiyang Yu 005; Maho Nakata; Jianwen Xie; Emine Küçükbenli; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusion. - Qingcheng Zhao; Xiang Zhang 015; Haiyang Xu 002; Zeyuan Chen; Jianwen Xie; Yuan Gao; Zhuowen Tu (CoRR, 2025)