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On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions


Feb 03, 2023
Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu, Kun Zhang

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Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data


Jan 25, 2023
Devansh Arpit, Matthew Fernandez, Chenghao Liu, Weiran Yao, Wenzhuo Yang, Paul Josel, Shelby Heinecke, Eric Hu, Huan Wang, Stephen Hoi, Caiming Xiong, Kun Zhang, Juan Carlos Niebles

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Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees


Jan 25, 2023
Yijun Bian, Kun Zhang

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* 18 pages, 15 figures, and 6 tables 

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Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors


Jan 21, 2023
Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang

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* The 11th International Conference on Learning Representations (ICLR 2023) 

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SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model


Dec 09, 2022
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, Kun Zhang

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Causal Discovery in Linear Latent Variable Models Subject to Measurement Error


Nov 08, 2022
Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser

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* Accepted at 36th Conference on Neural Information Processing Systems (NeurIPS 2022) 

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Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks


Nov 01, 2022
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

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* Work in progress 

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Temporally Disentangled Representation Learning


Oct 24, 2022
Weiran Yao, Guangyi Chen, Kun Zhang

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* NeurIPS 2022. arXiv admin note: text overlap with arXiv:2202.04828 

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Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations


Oct 12, 2022
Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao

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