Zhen Liu

According to our database, Zhen Liu authored at least 30 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Can Large Language Models Understand Symbolic Graphics Programs?

Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf

CoRR, 2024

PuzzleAvatar: Assembling 3D Avatars from Personal Albums.

Yuliang Xiu, Yufei Ye, Zhen Liu, Dimitrios Tzionas, Michael J. Black

CoRR, 2024

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Ghost on the Shell: An Expressive Representation of General 3D Shapes.

Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Continual Learning by Modeling Intra-Class Variation.

Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu

Trans. Mach. Learn. Res., 2023

Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods.

Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni

Trans. Mach. Learn. Res., 2023

Controlling Text-to-Image Diffusion by Orthogonal Finetuning.

Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MeshDiffusion: Score-based Generative 3D Mesh Modeling.

Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Iterative Teaching by Data Hallucination.

Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning.

Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni

CoRR, 2022

Generative Flow Networks for Discrete Probabilistic Modeling.

Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2022

Structural Causal 3D Reconstruction.

Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning.

Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Iterative Teaching by Label Synthesis.

Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Orthogonal Over-Parameterized Training.

Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Learning with Hyperspherical Uniformity.

Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Orthogonal Over-Parameterized Training.

Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Li Xiong, Le Song

CoRR, 2020

Regularizing Neural Networks via Minimizing Hyperspherical Energy.

Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Compressive Hyperspherical Energy Minimization.

Rongmei Lin, Weiyang Liu, Zhen Liu, Chen Feng, Zhiding Yu, James M. Rehg, Li Xiong, Le Song

CoRR, 2019

Neural Similarity Learning.

Weiyang Liu, Zhen Liu, James M. Rehg, Le Song

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Exponential Family Estimation via Adversarial Dynamics Embedding.

Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Learning towards Minimum Hyperspherical Energy.

Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Coupled Variational Bayes via Optimization Embedding.

Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Forward and Inverse Perceptual Models for Tracking and Prediction.

Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Towards Black-box Iterative Machine Teaching.

Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation.

Bo Dai, Albert E. Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

Decoupled Networks.

Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James M. Rehg, Le Song

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Deep Hyperspherical Learning.

Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

One-Shot Learning for Semantic Segmentation.

Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Multi Robot Object-Based SLAM.

Siddharth Choudhary, Luca Carlone, Carlos Nieto, John G. Rogers III, Zhen Liu, Henrik I. Christensen, Frank Dellaert

Proceedings of the International Symposium on Experimental Robotics, 2016