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2020 – today
- 2024
[c40]Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao:
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. ICLR 2024- [i41]Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu:
Latent Plan Transformer: Planning as Latent Variable Inference. CoRR abs/2402.04647 (2024) - [i40]Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu:
Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer. CoRR abs/2402.17179 (2024) - [i39]Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu:
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. CoRR abs/2405.16730 (2024) - [i38]Sheng Cheng, Deqian Kong, Jianwen Xie, Kookjin Lee, Ying Nian Wu, Yezhou Yang:
Latent Space Energy-based Neural ODEs. CoRR abs/2409.03845 (2024) - 2023
- [j10]Jing Zhang
, Jianwen Xie, Nick Barnes, Ping Li:
An Energy-Based Prior for Generative Saliency. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13100-13116 (2023) - [j9]Yifei Xu, Jianwen Xie, Tianyang Zhao, Chris L. Baker, Yibiao Zhao, Ying Nian Wu:
Energy-Based Continuous Inverse Optimal Control. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10563-10577 (2023) - [c39]Jianwen Xie, Yaxuan Zhu, Yifei Xu, Dingcheng Li, Ping Li:
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-Run Langevin Flow for Approximate Inference. AAAI 2023: 10499-10509 - [c38]Yang Zhao, Jianwen Xie, Ping Li:
CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning. AAAI 2023: 11345-11353 - [c37]Yaxuan Zhu, Jianwen Xie, Ping Li:
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation. AISTATS 2023: 4164-4180 - [i37]Jianwen Xie, Yaxuan Zhu, Yifei Xu, Dingcheng Li, Ping Li:
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference. CoRR abs/2301.09300 (2023) - [i36]Yang Zhao, Jianwen Xie, Ping Li:
CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning. CoRR abs/2303.11649 (2023) - [i35]Yaxuan Zhu, Jianwen Xie, Ping Li:
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation. CoRR abs/2304.07918 (2023) - [i34]Weinan Song, Yaxuan Zhu, Lei He, Yingnian Wu, Jianwen Xie:
Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation. CoRR abs/2306.14448 (2023) - [i33]Yaxuan Zhu, Jianwen Xie, Yingnian Wu, Ruiqi Gao:
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. CoRR abs/2309.05153 (2023) - [i32]Deqian Kong, Yuhao Huang, Jianwen Xie, Ying Nian Wu:
Molecule Design by Latent Prompt Transformer. CoRR abs/2310.03253 (2023) - [i31]Belhal Karimi, Jianwen Xie, Ping Li:
STANLEY: Stochastic Gradient Anisotropic Langevin Dynamics for Learning Energy-Based Models. CoRR abs/2310.12667 (2023) - 2022
- [j8]Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu:
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2468-2484 (2022) - [j7]Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu:
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 3957-3973 (2022) - [j6]Yuanlu Xu, Wenguan Wang, Tengyu Liu, Xiaobai Liu, Jianwen Xie, Song-Chun Zhu:
Monocular 3D Pose Estimation via Pose Grammar and Data Augmentation. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6327-6344 (2022) - [c36]Jing Zhang, Jianwen Xie, Zilong Zheng, Nick Barnes:
Energy-Based Generative Cooperative Saliency Prediction. AAAI 2022: 3280-3290 - [c35]Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu:
Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion. AAAI 2022: 6674-6684 - [c34]Zongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang, Deyu Meng, Kwan-Yee K. Wong:
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel. CVPR 2022: 2118-2128 - [c33]Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li:
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model. ICLR 2022 - [i30]Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li:
An Energy-Based Prior for Generative Saliency. CoRR abs/2204.08803 (2022) - [i29]Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li:
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model. CoRR abs/2205.06924 (2022) - [i28]Khoa D. Doan, Jianwen Xie, Yaxuan Zhu, Yang Zhao, Ping Li:
CoopHash: Cooperative Learning of Multipurpose Descriptor and Contrastive Pair Generator via Variational MCMC Teaching for Supervised Image Hashing. CoRR abs/2210.04288 (2022) - 2021
- [j5]Wenguan Wang, Jianbing Shen, Jianwen Xie, Ming-Ming Cheng, Haibin Ling, Ali Borji:
Revisiting Video Saliency Prediction in the Deep Learning Era. IEEE Trans. Pattern Anal. Mach. Intell. 43(1): 220-237 (2021) - [j4]Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 516-531 (2021) - [c32]Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu:
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. AAAI 2021: 10430-10440 - [c31]Jianwen Xie, Zilong Zheng, Ping Li:
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler. AAAI 2021: 10441-10451 - [c30]Tan Yu, Xiaokang Li, Jianwen Xie, Ruiyang Yin, Qing Xu, Ping Li:
MixBERT for Image-Ad Relevance Scoring in Advertising. CIKM 2021: 3597-3602 - [c29]Zongsheng Yue, Jianwen Xie, Qian Zhao, Deyu Meng:
Semi-Supervised Video Deraining With Dynamical Rain Generator. CVPR 2021: 642-652 - [c28]Zilong Zheng, Jianwen Xie, Ping Li:
Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning. CVPR 2021: 2961-2970 - [c27]Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. CVPR 2021: 14976-14985 - [c26]Dongsheng An, Jianwen Xie, Ping Li:
Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction. CVPR 2021: 15415-15424 - [c25]Yang Zhao, Jianwen Xie, Ping Li:
Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling. ICLR 2021 - [c24]Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li:
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction. NeurIPS 2021: 15448-15463 - [c23]Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu:
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. NeurIPS 2021: 28623-28635 - [i27]Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu:
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. CoRR abs/2103.04285 (2021) - [i26]Zongsheng Yue, Jianwen Xie, Qian Zhao, Deyu Meng:
Semi-Supervised Video Deraining with Dynamical Rain Generator. CoRR abs/2103.07939 (2021) - [i25]Jing Zhang, Jianwen Xie, Zilong Zheng, Nick Barnes:
Energy-Based Generative Cooperative Saliency Prediction. CoRR abs/2106.13389 (2021) - [i24]Zongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang, Deyu Meng:
Unsupervised Single Image Super-resolution Under Complex Noise. CoRR abs/2107.00986 (2021) - [i23]Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li:
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction. CoRR abs/2112.13528 (2021) - 2020
- [j3]Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu:
Cooperative Training of Descriptor and Generator Networks. IEEE Trans. Pattern Anal. Mach. Intell. 42(1): 27-45 (2020) - [c22]Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. AAAI 2020: 12442-12451 - [c21]Jing Zhang, Jianwen Xie, Nick Barnes:
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection. ECCV (17) 2020: 349-366 - [i22]Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. CoRR abs/2004.01301 (2020) - [i21]Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
A Representational Model of Grid Cells Based on Matrix Lie Algebras. CoRR abs/2006.10259 (2020) - [i20]Jing Zhang, Jianwen Xie, Nick Barnes:
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection. CoRR abs/2007.12211 (2020) - [i19]Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu:
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. CoRR abs/2012.13522 (2020) - [i18]Jianwen Xie, Zilong Zheng, Ping Li:
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler. CoRR abs/2012.14936 (2020)
2010 – 2019
- 2019
- [c20]Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Learning Dynamic Generator Model by Alternating Back-Propagation through Time. AAAI 2019: 5498-5507 - [c19]Yunlu Xu, Chengwei Zhang, Zhanzhan Cheng, Jianwen Xie, Yi Niu, Shiliang Pu, Fei Wu:
Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection. AAAI 2019: 9070-9078 - [c18]Yizhe Zhu, Jianwen Xie, Bingchen Liu, Ahmed Elgammal:
Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning. ICCV 2019: 9843-9853 - [c17]Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion. ICLR (Poster) 2019 - [c16]Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal:
Semantic-Guided Multi-Attention Localization for Zero-Shot Learning. NeurIPS 2019: 14917-14927 - [i17]Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu:
Multimodal Conditional Learning with Fast Thinking Policy-like Model and Slow Thinking Planner-like Model. CoRR abs/1902.02812 (2019) - [i16]Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1. CoRR abs/1902.03871 (2019) - [i15]Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal:
Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning. CoRR abs/1903.00502 (2019) - [i14]Zhanzhan Cheng, Jing Lu, Jianwen Xie, Yi Niu, Shiliang Pu, Fei Wu:
Efficient Video Scene Text Spotting: Unifying Detection, Tracking, and Recognition. CoRR abs/1903.03299 (2019) - [i13]Yizhe Zhu, Jianwen Xie, Bingchen Liu, Ahmed Elgammal:
Learning Feature-to-Feature Translator by Alternating Back-Propagation for Zero-Shot Learning. CoRR abs/1904.10056 (2019) - [i12]Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns. CoRR abs/1909.11975 (2019) - [i11]Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. CoRR abs/1911.11294 (2019) - [i10]Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu:
Representation Learning: A Statistical Perspective. CoRR abs/1911.11374 (2019) - 2018
- [c15]Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu:
Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching. AAAI 2018: 4292-4301 - [c14]Haoshu Fang, Guansong Lu, Xiaolin Fang, Jianwen Xie, Yu-Wing Tai, Cewu Lu:
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer. CVPR 2018: 70-78 - [c13]Yuanlu Xu, Lei Qin, Xiaobai Liu, Jianwen Xie, Song-Chun Zhu:
A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects. CVPR 2018: 2178-2187 - [c12]Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu:
Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CVPR 2018: 8629-8638 - [i9]Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu:
Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CoRR abs/1804.00586 (2018) - [i8]Haoshu Fang, Guansong Lu, Xiaolin Fang, Jianwen Xie, Yu-Wing Tai, Cewu Lu:
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer. CoRR abs/1805.04310 (2018) - [i7]Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion. CoRR abs/1810.05597 (2018) - [i6]Yunlu Xu, Chengwei Zhang, Zhanzhan Cheng, Jianwen Xie, Yi Niu, Shiliang Pu, Fei Wu:
Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection. CoRR abs/1811.07460 (2018) - [i5]Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu:
Learning Dynamic Generator Model by Alternating Back-Propagation Through Time. CoRR abs/1812.10587 (2018) - 2017
- [c11]Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet. CVPR 2017: 1061-1069 - [c10]Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu:
Generative Hierarchical Learning of Sparse FRAME Models. CVPR 2017: 1933-1941 - [c9]Wenguan Wang, Jianbing Shen, Jianwen Xie, Fatih Porikli:
Super-Trajectory for Video Segmentation. ICCV 2017: 1680-1688 - 2016
- [b1]Jianwen Xie:
Generative Modeling and Unsupervised Learning in Computer Vision. University of California, Los Angeles, USA, 2016 - [c8]Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu:
A Theory of Generative ConvNet. ICML 2016: 2635-2644 - [i4]Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu:
A Theory of Generative ConvNet. CoRR abs/1602.03264 (2016) - [i3]Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet. CoRR abs/1606.00972 (2016) - [i2]Jianwen Xie, Pamela K. Douglas, Ying Nian Wu, Arthur L. Brody, Ariana E. Anderson:
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. CoRR abs/1607.00435 (2016) - [i1]Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu:
Cooperative Training of Descriptor and Generator Networks. CoRR abs/1609.09408 (2016) - 2015
- [j2]Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu:
Learning Sparse FRAME Models for Natural Image Patterns. Int. J. Comput. Vis. 114(2-3): 91-112 (2015) - 2014
- [j1]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:
Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD. NeuroImage 102: 207-219 (2014) - [c7]Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu:
Learning Inhomogeneous FRAME Models for Object Patterns. CVPR 2014: 1035-1042
2000 – 2009
- 2009
- [c6]Jianwen Xie, Jianhua Wu, Qingquan Qian:
Feature Selection Algorithm Based on Association Rules Mining Method. ACIS-ICIS 2009: 357-362 - [c5]Weigang Jiang, Yuanbiao Zhang, Jianwen Xie:
A particle swarm optimization algorithm with crossover for vehicle routing problem with time windows. CISched 2009: 103-106 - [c4]Jianwen Xie, Xiaoxiang Liu, Weigang Jiang:
Linear Programming With Fuzzy Relation Constraints: A Molecular-Diffusion Based Particle Swarm Optimization Approach. IC-AI 2009: 242-248 - [c3]Jianwen Xie, Weigang Jiang, Xiaoxiang Liu:
Feature Subset Selection Using Association Rules. IC-AI 2009: 362-368 - [c2]Xiaoxiang Liu, Weigang Jiang, Jianwen Xie:
Vehicle Routing Problem with Time Windows: A Hybrid Particle Swarm Optimization Approach. ICNC (4) 2009: 502-506 - [c1]Ming Li, Yuanbiao Zhang, Weigang Jiang, Jianwen Xie:
A Particle Swarm Optimization Algorithm with Crossover for Resource Constrained Project Scheduling Problem. SSME 2009: 69-72
Coauthor Index
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