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Zhen Liu 0019
Person information
- affiliation: Mila - Quebec AI Institute, Montreal, QC, Canada
- affiliation: University of Montreal, Montreal, QC, Canada
- affiliation: Georgia Institute of Technology, Atlanta, GA, USA
Other persons with the same name
- Zhen Liu — disambiguation page
- Zhen Liu 0001 — Nokia Research Center, Beijing, China (and 4 more)
- Zhen Liu 0002
— Ningbo University, Faculty of Information Science and Technology, Ningbo, China (and 2 more)
- Zhen Liu 0003
— University of Electronic Science and Technology of China, School of Automation Engineering, Chengdu, China (and 1 more)
- Zhen Liu 0004
— National University of Defense Technology, College of Electronic Science and Engineering, Changsha, China
- Zhen Liu 0005
— Chinese Academy of Sciences, Institute of Microelectronics, Beijing, China
- Zhen Liu 0006
— University of Electronic Science and Technology of China, School of Computer Science and Engineering, Web Sciences Center / Big Data Research Center, Chengdu, China
- Zhen Liu 0007
— California Institute of Technology, Jet Propulsion Laboratory, Pasadena, CA, USA (and 1 more)
- Zhen Liu 0008
— City University of Hong Kong, Department of Computer Science, Hong Kong (and 1 more)
- Zhen Liu 0009
— Armed Police Force Engineering University, College of Cryptography Engineering, Xi'an, China
- Zhen Liu 0010
— Shanghai Jiao Tong University, State Key Laboratory of Mechanical System and Vibration, Shanghai, China
- Zhen Liu 0011
— Sun Yat-sen University, School of Civil Engineering, Guangzhou, China
- Zhen Liu 0012 — Ningbo University, Faculty of Electrical Engineering and Computer Science, Ningbo, China
- Zhen Liu 0013
— Guangdong University of Technology, School of Materials and Energy, Guangzhou, China
- Zhen Liu 0014
— Harbin Institute of Technology, School of Mechatronics Engineering, State Key Laboratory of Robotics and System, Harbin, China
- Zhen Liu 0015
— Jiangnan University, School of Internet of Things Engineering, Wuxi, China
- Zhen Liu 0016
— Beihang University, School of Instrumentation Science and Opto-Electronics Engineering, Key Laboratory of Precision Opto-Mechatronics Technology, Beijing, China
- Zhen Liu 0017
— Guangdong Pharmaceutical University, School of Medical Information Engineering, Guangzhou, China (and 1 more)
- Zhen Liu 0018 — Dublin City University, School of Electronic Engineering, Dublin, Ireland (and 1 more)
- Zhen Liu 0020
— Chinese Academy of Sciences, Institute of Automation, Beijing, China
- Zhen Liu 0021 — Henan Institute of Science and Technology, Network Center, Xinxiang, China
- Zhen Liu 0022
— University of Electronic Science and Technology of China, Chengdu, China (and 1 more)
- Zhen Liu 0023
— South China University of Technology, Guangzhou, China
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2020 – today
- 2024
- [j3]Yuliang Xiu
, Yufei Ye
, Zhen Liu
, Dimitris Tzionas
, Michael J. Black
:
PuzzleAvatar: Assembling 3D Avatars from Personal Albums. ACM Trans. Graph. 43(6): 283:1-283:15 (2024) - [c23]Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf:
Ghost on the Shell: An Expressive Representation of General 3D Shapes. ICLR 2024 - [c22]Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf:
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. ICLR 2024 - [i24]Yuliang Xiu, Yufei Ye, Zhen Liu, Dimitrios Tzionas, Michael J. Black:
PuzzleAvatar: Assembling 3D Avatars from Personal Albums. CoRR abs/2405.14869 (2024) - [i23]Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Can Large Language Models Understand Symbolic Graphics Programs? CoRR abs/2408.08313 (2024) - [i22]Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang:
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. CoRR abs/2412.07775 (2024) - [i21]Siyuan Bian, Chenghao Xu, Yuliang Xiu, Artur Grigorev, Zhen Liu, Cewu Lu, Michael J. Black, Yao Feng:
ChatGarment: Garment Estimation, Generation and Editing via Large Language Models. CoRR abs/2412.17811 (2024) - 2023
- [j2]Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni:
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf:
Iterative Teaching by Data Hallucination. AISTATS 2023: 9892-9913 - [c20]Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu:
MeshDiffusion: Score-based Generative 3D Mesh Modeling. ICLR 2023 - [c19]Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf:
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. NeurIPS 2023 - [i20]Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu:
MeshDiffusion: Score-based Generative 3D Mesh Modeling. CoRR abs/2303.08133 (2023) - [i19]Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf:
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. CoRR abs/2306.07280 (2023) - [i18]Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf:
Ghost on the Shell: An Expressive Representation of General 3D Shapes. CoRR abs/2310.15168 (2023) - [i17]Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf:
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. CoRR abs/2311.06243 (2023) - 2022
- [c18]Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf:
Structural Causal 3D Reconstruction. ECCV (1) 2022: 140-159 - [c17]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. ICML 2022: 26412-26428 - [i16]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. CoRR abs/2202.01361 (2022) - [i15]Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni:
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning. CoRR abs/2206.01251 (2022) - [i14]Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf:
Structural Causal 3D Reconstruction. CoRR abs/2207.10156 (2022) - [i13]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. CoRR abs/2210.05398 (2022) - [i12]Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf:
Iterative Teaching by Data Hallucination. CoRR abs/2210.17467 (2022) - 2021
- [c16]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. AISTATS 2021: 1180-1188 - [c15]Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller:
Orthogonal Over-Parameterized Training. CVPR 2021: 7251-7260 - [c14]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. NeurIPS 2021: 1569-1581 - [c13]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. NeurIPS 2021: 21681-21695 - [i11]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. CoRR abs/2103.01649 (2021) - [i10]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. CoRR abs/2106.02097 (2021) - [i9]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. CoRR abs/2110.14432 (2021) - 2020
- [c12]Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng
, Zhiding Yu, James M. Rehg, Li Xiong
, Le Song:
Regularizing Neural Networks via Minimizing Hyperspherical Energy. CVPR 2020: 6916-6925 - [i8]Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Li Xiong, Le Song:
Orthogonal Over-Parameterized Training. CoRR abs/2004.04690 (2020)
2010 – 2019
- 2019
- [c11]Weiyang Liu, Zhen Liu, James M. Rehg, Le Song:
Neural Similarity Learning. NeurIPS 2019: 5026-5037 - [c10]Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans:
Exponential Family Estimation via Adversarial Dynamics Embedding. NeurIPS 2019: 10977-10988 - [i7]Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans:
Exponential Family Estimation via Adversarial Dynamics Embedding. CoRR abs/1904.12083 (2019) - [i6]Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song:
Compressive Hyperspherical Energy Minimization. CoRR abs/1906.04892 (2019) - [i5]Weiyang Liu, Zhen Liu, James M. Rehg, Le Song:
Neural Similarity Learning. CoRR abs/1910.13003 (2019) - 2018
- [c9]Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg
, Le Song:
Decoupled Networks. CVPR 2018: 2771-2779 - [c8]Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song:
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation. ICML 2018: 1133-1142 - [c7]Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg
, Le Song:
Towards Black-box Iterative Machine Teaching. ICML 2018: 3147-3155 - [c6]Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots:
Deep Forward and Inverse Perceptual Models for Tracking and Prediction. ICRA 2018: 675-682 - [c5]Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song:
Learning towards Minimum Hyperspherical Energy. NeurIPS 2018: 6225-6236 - [c4]Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song:
Coupled Variational Bayes via Optimization Embedding. NeurIPS 2018: 9713-9723 - [i4]Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song:
Decoupled Networks. CoRR abs/1804.08071 (2018) - [i3]Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song:
Learning towards Minimum Hyperspherical Energy. CoRR abs/1805.09298 (2018) - 2017
- [c3]Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots:
One-Shot Learning for Semantic Segmentation. BMVC 2017 - [c2]Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song:
Deep Hyperspherical Learning. NIPS 2017: 3950-3960 - [i2]Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots:
One-Shot Learning for Semantic Segmentation. CoRR abs/1709.03410 (2017) - [i1]Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots:
Deep Forward and Inverse Perceptual Models for Tracking and Prediction. CoRR abs/1710.11311 (2017) - 2016
- [c1]Siddharth Choudhary, Luca Carlone, Carlos Nieto, John G. Rogers III, Zhen Liu, Henrik I. Christensen
, Frank Dellaert:
Multi Robot Object-Based SLAM. ISER 2016: 729-741
Coauthor Index

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last updated on 2025-02-18 01:18 CET by the dblp team
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