Jianwen Xie 谢建文

• I am a research scientist in artificial intelligence, mainly interested in Generative models, Language Model, AI Generated Contents, AI for science, and embodied AI. I received my Ph.D. in Statistics at University of California, Los Angeles (UCLA), under the supervision of Prof. Ying Nian Wu and Prof. Song-Chun Zhu.

• [02/2025] I will serve as a Senior Area Chair for NeurIPS 2025
• [11/2024] I am honored to receive IEEE TNNLS Outstanding Associate Editor Award.
• [11/2024] I will serve as an Area Chair for ICML 2025

• University of California, Los Angeles, USA
Ph.D. in Statistics, 2016
Master of Science in Statistics, 2014
Master of Science in Computer Science, 2012

Associate Editor:

Senior Area Chair:

Area Chair:

Senior Program Committee:

• 1. Organizer & Speaker -- CVPR 2021 Tutorial on Theory and Application of Energy-Based Generative Models [page]
• 2. Organizer & Speaker -- ICCV 2021 Tutorial on Theory and Application of Energy-Based Generative Models [page]
• 3. Organizer & Speaker -- IJCAI 2022 Tutorial on Deep Energy-Based Learning [page]
• 4. Organizer & Speaker -- ECCV 2022 Tutorial on Deep Energy-Based Learning in Computer Vision [page]
• 5. Organizer -- CVPR 2025 Workshop on LOVE: Multimodal Video Agent [page]
• 6. Organizer -- NeurIPS 2025 Workshop on Bridging Language, Agent, and World Models for Reasoning and Planning [page]
• 7. Organizer -- CVPR 2026 Workshop on World Models Meet Active Sensing and Closed-Loop Planning [page]
• 8. Organizer -- CVPR 2026 Workshop on Rediscovering Intelligence: Can AI Still Learn From Humans? [page]

• Generative Modeling and Unsupervised Learning in Computer Vision, University of California, Los Angeles, 2016

In-The-Flow Agentic System Optimization for Effective Planning and Tool Use
• --Zhuofeng Li, Haoxiang Zhang, Seungju Han, Sheng Liu, Jianwen Xie, Yu Zhang, Yejin Choi, James Zou, Pan Lu
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing
• --Tianyu Chen, Yasi Zhang, Zhi Zhang, Peiyu Yu, Shu Wang, Zhendong Wang, Kevin Lin, Xiaofei Wang, Zhengyuan Yang, Linjie Li, Chung-Ching Lin, Jianwen Xie, Oscar Leong, Lijuan Wang, Ying Nian Wu, Mingyuan Zhou
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics
• --Aniketh Iyengar, Jiaqi Han, Pengwei Sun, Mingjian Jiang, Jianwen Xie, Stefano Ermon
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective
• --Jingyang Ou, Jiaqi Han, Minkai Xu, Shaoxuan Xu, Jianwen Xie, Stefano Ermon, Yi Wu, Chongxuan Li
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• VideoNSA: Native Sparse Attention Scales Video Understanding
• --Enxin Song, Wenhao Chai, Shusheng Yang, Ethan J. Armand, Xiaojun Shan, Haiyang Xu, Jianwen Xie, Zhuowen Tu
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration
• --Zeyu Yang, Tianyi Zhang, Jianwen Xie, Chuan Li, Zhaozhuo Xu, Anshumali Shrivastava
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning
• --Ziwen Liu, Huawei Lin, Yide Ran, Denghui Zhang, Jianwen Xie, Chuan Li, Weijie Zhao, Zhaozhuo Xu
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity
• --Yide Ran, Wentao Guo, Jingwei Sun, Yanzhou Pan, Xiaodong Yu, Hao Wang, Jianwen Xie, Yiran Chen, Denghui Zhang, Zhaozhuo Xu
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• "Noisier" Noise Contrastive Estimation is (Almost) Maximum Likelihood
• --Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Sirui Xie, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu
• --The Fourteenth International Conference on Learning Representations (ICLR) 2026


• CVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning [PDF]
• --Zeyuan Chen, Xiang Zhang, Haiyang Xu, Jianwen Xie, Zhuowen Tu
• --Winter Conference on Applications of Computer Vision (WACV) 2026


• Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials [PDF]
• --Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji
• --Transactions on Machine Learning Research (TMLR) 2026


• SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning [PDF]
• --Wufei Ma *, Yu-Cheng Chou *, Qihao Liu *, Xingrui Wang, Celso de Melo, Jianwen Xie, Alan Yuille (* equal contributions)
• --The Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS) 2025


• Tensor Decomposition Networks for Accelerating Machine Learning Force Field Computations [PDF]
• --Yuchao Lin *, Cong Fu *, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji (* equal contributions)
• --The Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS) 2025


• OverLayBench: A Benchmark for Layout-to-Image Generation with Dense Overlaps [PDF]
• --Bingnan Li *, Chen-Yu Wang *, Haiyang Xu *, Xiang Zhang, Ethan Armand, Divyansh Srivastava, Shan Xiaojun, Zeyuan Chen, Jianwen Xie, Zhuowen Tu (* equal contributions)
• --The Thirty-ninth Conference on Neural Information Processing Systems (NeurIPS D&B Track) 2025


• Word Salad Chopper: Reasoning Models Waste A Ton Of Decoding Budget On Useless Repetitions, Self-Knowingly [PDF]
• --Wenya Xie, Shaochen Zhong, Hoang Anh Duy Le, Zhaozhuo Xu, Jianwen Xie, Zirui Liu
• --The Conference on Empirical Methods in Natural Language Processing (EMNLP) 2025


• DEL-ToM: Inference-Time Scaling for Theory-of-Mind Reasoning via Dynamic Epistemic Logic [PDF]
• --Yuheng Wu, Jianwen Xie, Denghui Zhang, Zhaozhuo Xu
• --The Conference on Empirical Methods in Natural Language Processing (EMNLP) 2025


• Latent Adaptive Planner for Dynamic Manipulation [PDF]
• --Donghun Noh *, Deqian Kong *, Minglu Zhao, Andrew Lizarraga, Jianwen Xie, Ying Nian Wu ♣, Dennis Hong ♣ (* equal contributions, ♣ equal advising)
• --The Ninth Conference on Robot Learning (CoRL) 2025


• DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusion [PDF] [project page]
• --Qingcheng Zhao *, Xiang Zhang *, Haiyang Xu, Zeyuan Chen, Jianwen Xie, Yuan Gao, Zhuowen Tu (* equal contributions)
• --International Conference on Computer Vision (ICCV) 2025


• Latent Thought Models with Variational Bayes Inference-Time Computation [PDF] [project page]
• --Deqian Kong *, Minglu Zhao *, Dehong Xu *, Bo Pang, Shu Wang, Edouardo Honig, Zhangzhang Si, Chuan Li, Jianwen Xie ♣, Sirui Xie ♣, Ying Nian Wu ♣ (* equal contributions, ♣ equal advising)
• --The Forty-Second International Conference on Machine Learning (ICML) 2025


• Latent Space Energy-based Neural ODEs [PDF]
• --Sheng Cheng *, Deqian Kong *, Jianwen Xie, Kookjin Lee, Ying Nian Wu, Yezhou Yang
• --Transactions on Machine Learning Research (TMLR) 2025


• Molecule Design by Latent Prompt Transformer [PDF]
• --Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou. Sheng Zhong, Nanning Zheng, Ying Nian Wu
• --Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS) 2024
• (an expanded version of the NeurIPS-23 workshop paper [PDF] on AI for science)


• Latent Plan Transformer: Planning as Latent Variable Inference [PDF]
• --Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu
• --Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS) 2024


• Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood [PDF]
• --Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao
• --The Twelfth International Conference on Learning Representations (ICLR) 2024


• An Energy-Based Prior for Generative Saliency [PDF]
• --Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023
• (an expanded version of the NeurIPS-21 paper for generative saliency)


• Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation [PDF] [code]
• --Yaxuan Zhu, Jianwen Xie, Ping Li
• --The Twenty-Sixth International Conference on Artificial Intelligence and Statistics (AISTATS) 2023


• A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference [PDF] [project page]
• --Jianwen Xie, Yaxuan Zhu, Yifei Xu, Dingcheng Li, Ping Li
• --The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI) 2023


• CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning [PDF]
• --Yang Zhao, Jianwen Xie, Ping Li
• --The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI) 2023


• Energy-Based Continuous Inverse Optimal Control [PDF] [project page]
• --Yifei Xu, Jianwen Xie, Tianyang Zhao, Chris Baker, Yibiao Zhao, Ying Nian Wu
• --IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2022
• (an expanded version of the NeurIPS 2020 workshop paper on machine learning for autonomous driving)


• Blind Image Super-Resolution with Elaborate Degradation Modeling on Noise and Kernel [PDF]
• --Zongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang, Deyu Meng, Kwan-Yee K. Wong
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022


• A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model [PDF] [project page]
• --Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li
• --Tenth International Conference on Learning Representations (ICLR) 2022


• Learning V1 Simple Cells with Vector Representations of Local Contents and Matrix Representations of Local Motions [PDF] [project page]
• --Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu
• --The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI) 2022


• Energy-Based Generative Cooperative Saliency Prediction [PDF]
• --Jing zhang, Jianwen Xie, Zilong Zheng, Nick Barnes
• --The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI) 2022


• On Path Integration of Grid Cells: Group Representation and Isotropic Scaling [PDF]
• --Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu
• --Thirty-fifth Annual Conference on Neural Information Processing Systems (NeurIPS) 2021


• Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction [PDF]
• --Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li
• --Thirty-fifth Annual Conference on Neural Information Processing Systems (NeurIPS) 2021


• Monocular 3D Pose Estimation via Pose Grammar and Data Augmentation [PDF]
• --Yuanlu Xu, Wenguan Wang, Tengyu Liu, Xiaobai Liu, Jianwen Xie, Song-Chun Zhu
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021


• Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning [PDF] [project page]
• --Jianwen Xie *, Zilong Zheng *, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021


• Patchwise Generative ConvNet: Training Energy-Based Models from a Single Natural Image for Internal Learning [PDF] [project page]
• --Zilong Zheng, Jianwen Xie, Ping Li
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021 (Oral)


• Learning Deep Latent Variable Models by Short-Run MCMC Inference with Optimal Transport Correction [PDF]
• --Dongsheng An, Jianwen Xie, Ping Li
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021


• Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification [PDF] [project page]
• --Jianwen Xie *, Yifei Xu *, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021


• Semi-Supervised Video Deraining with Dynamical Rain Generator [PDF]
• --Zongsheng Yue, Jianwen Xie, Qian Zhao, Deyu Meng
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021


• Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling [PDF] [code]
• --Yang Zhao, Jianwen Xie, Ping Li
• --Ninth International Conference on Learning Representations (ICLR) 2021


• Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation [PDF] [project page]
• --Jianwen Xie *, Zilong Zheng *, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) 2021


• Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler [PDF] [project page]
• --Jianwen Xie, Zilong Zheng, Ping Li
• --The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) 2021


• Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis [PDF] [project page]
• --Jianwen Xie *, Zilong Zheng *, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2020
• (an expanded version of the CVPR-18 paper for energy-based 3D descriptor network)


• Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection [PDF]
• --Jing Zhang, Jianwen Xie, Nick Barnes
• --European Conference on Computer Vision (ECCV) 2020


• Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns [PDF][project page]
• --Jianwen Xie *, Ruiqi Gao *, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI) 2020 (Oral)


• Representation Learning: A Statistical Perspective [PDF][Tex]
• --Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
• --Annual Review of Statistics and Its Application (ARSIA) 2020
• (an review article on the subject of Representation Learning to Annual Reviews, whose Impact Factor rankings are among the highest in scholarly publishing)
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• Learning Energy-based Spatial-Temporal Generative ConvNet for Dynamic Patterns [PDF] [project page]
• --Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019
• (an expanded version of the CVPR-17 paper for spatial-temporal generative ConvNet)


• Revisiting Video Saliency Prediction in the Deep Learning Era [PDF]
• --Wenguan Wang, Jianbing Shen, Jianwen Xie, Ming-Ming Cheng, Haibin Ling, Ali Borji
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019


• Semantic-Guided Multi-Attention Localization for Zero-Shot Learning [PDF]
• --Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal
• --Thirty-third Conference on Neural Information Processing Systems (NeurIPS) 2019


• Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning [PDF]
• --Yizhe Zhu, Jianwen Xie, Bingchen Liu, Ahmed Elgammal
• --International Conference on Computer Vision (ICCV) 2019


• Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion [PDF][project page]
• --Ruiqi Gao *, Jianwen Xie *, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --Seventh International Conference on Learning Representations (ICLR) 2019


• Learning Dynamic Generator Model by Alternating Back-Propagation Through Time [PDF][project page]
• --Jianwen Xie *, Ruiqi Gao *, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) 2019 (Spotlight)


• Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection
• --Yunlu Xu, Chengwei Zhang, Zhanzhan Cheng, Jianwen Xie, Yi Niu, Shiliang Pu, Fei Wu
• --The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) 2019 (Oral)


• Cooperative Training of Descriptor and Generator Networks [PDF][project page]
• --Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
• --IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018
• (an expanded version of the AAAI-18 paper for cooperative learning)


• Learning Descriptor Networks for 3D Shape Synthesis and Analysis [PDF][project page]
• --Jianwen Xie *, Zilong Zheng *, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 (Oral)


• A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects [PDF]
• --Yuanlu Xu *, Lei Qin *, Xiaobai Liu, Jianwen Xie, Song-Chun Zhu (* equal contributions)
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018


• Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer [PDF]
• --Hao-Shu Fang, Guansong Lu, Xiaolin Fang, Jianwen Xie, Yu-Wing Tai, Cewu Lu
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 (Spotlight)


• Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching [PDF][project page]
• --Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu
• --The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) 2018 (Oral)


• Sparse and Deep Generalizations of the FRAME Model [PDF][Tex]
• --Ying Nian Wu, Jianwen Xie, Yang Lu, Song-Chun Zhu
• --Annals of Mathematical Sciences and Applications (AMSA) 2018
• (an invited paper to the AMSA special issue in honor of Professor David Mumford on his 80th birthday)


• Super-Trajectory for Video Segmentation [PDF]
• --Wenguan Wang, Jianbing Shen, Jianwen Xie, Fatih Porikli
• --International Conference on Computer Vision (ICCV) 2017


• Synthesizing Dynamic Pattern by Spatial-Temporal Generative ConvNet [PDF][project page]
• --Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017


• Generative Hierarchical Learning of Sparse FRAME Models [PDF][project page]
• --Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017


• 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 [PDF]
• --Jianwen Xie, Pamela K. Douglas, Ying Nian Wu, Arthur L. Brody, Ariana E. Anderson
• --Journal of Neuroscience Methods 2017


• A Theory of Generative ConvNet [PDF]
• --Jianwen Xie *, Yang Lu *, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• (an expanded version of the ICML-16 paper written for statisticians.)


• A Theory of Generative ConvNet [PDF][project page]
• --Jianwen Xie *, Yang Lu *, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
• --International Conference on Machine Learning (ICML) 2016 (Oral)


• Inducing Wavelets into Random Fields via Generative Boosting [PDF][project page]
• --Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu
• --Journal of Applied and Computational Harmonic Analysis (ACHA) 2015
• (ACHA is a premier journal in harmonic analysis and applied mathematics)


• Learning Sparse FRAME Models for Natural Image Patterns [PDF][project page]
• --Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
• --International Journal of Computer Vision (IJCV) 2014


• Learning Inhomogeneous FRAME Models for Object Patterns [PDF][project page]
• --Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
• --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014


• Non-negative Matrix Factorization of Multimodal MRI, fMRI and Phenotypic Data reveals Differential Changes in Default Mode Subnetworks in ADHD [PDF]
• --Ariana Anderson, Pamela Douglas, Wesley Kerr, Virginia Haynes, Alan Yuille, Jianwen Xie, Ying Nian Wu, Jesse Brown, Mark Cohen
• --NeuroImage 2014.