Linqi (Alex) Zhou

Linqi (Alex) Zhou

Ph.D. Student @ Stanford University

About Me

I am a Research Scientist at Luma AI. I am also a Ph.D. student (on leave) at Stanford University advised by Prof. Stefano Ermon. I previously received my bachelor’s degrees in Computer Science and Applied Mathematics at University of California, Los Angeles and was advised by Prof. Song-Chun Zhu and Prof. Ying-Nian Wu. I work on machine learning methods for generative modeling.

I was a co-founder at Apparate Labs (acquired by Luma AI) focusing on real-time visual synthesis of human-centric videos.


Publications

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Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillation
Aaditya Prasad, Kevin Lin, Jimmy Wu, Linqi Zhou, Jeannette Bohg
RSS 2024
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DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling
Linqi Zhou, Andy Shih, Chenlin Meng, Stefano Ermon
CVPR 2024 (Highlight)
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Diffusion Model Alignment Using Direct Preference Optimization
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
CVPR 2024
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DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David Lobell, Stefano Ermon
ICLR 2024
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Denoising Diffusion Bridge Models
Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
ICLR 2024
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AO-Grasp: Articulated Object Grasp Generation
Carlota Parés Morlans, Claire Chen, Yijia Weng, Michelle Yi, Yuying Huang, Nick Heppert, Linqi Zhou, Leonidas Guibas, Jeannette Bohg
arXiv 2023
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Deep Latent State Space Models for Time-Series Generation
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon
ICML 2023
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Curious Replay for Model-based Adaptation
Isaac Kauvar*, Chris Doyle*, Linqi Zhou, Nick Haber
ICML 2023
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ButterflyFlow: Building Invertible Layers with Butterfly Matrices
Chenlin Meng*, Linqi Zhou*, Kristy Choi*, Tri Dao, Stefano Ermon
ICML 2022
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3D Shape Generation and Completion through Point-Voxel Diffusion
Linqi Zhou, Yilun Du, Jiajun Wu
ICCV 2021 (Oral)
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Deep Unsupervised Clustering with Clustered Generator Model
Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu
In Submission
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Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference
Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu
ECCV 2020
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Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
Tian Han*, Erik Nijkamp*, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
CVPR 2020
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Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation
Bo Pang*, Erik Nijkamp*, Wenjuan Han*, Linqi Zhou*, Yixian Liu, Kewei Tu
ACL 2020
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Emergence of Theory of Mind Collaboration in Multiagent Systems
Luyao Yuan, Zipeng Fu, Linqi Zhou, Kexin Yang, Song-Chun Zhu
NeurIPS 2019 Workshop
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Neural Architecture Search for Joint Optimization of Predictive Power and Biological Knowledge
Zijun Zhang, Linqi Zhou, Liangke Gou, Ying Nian Wu
arXiv 2019
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