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High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning


Jun 16, 2021
Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar


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Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms


Jun 02, 2021
Yunqi Wang, Furui Liu, Zhitang Chen, Qing Lian, Shoubo Hu, Jianye Hao, Yik-Chung Wu


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Ordering-Based Causal Discovery with Reinforcement Learning


May 17, 2021
Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang

* Accepted to IJCAI'2021 

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Causal World Models by Unsupervised Deconfounding of Physical Dynamics


Dec 28, 2020
Minne Li, Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jun Wang


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Disentangled Generative Causal Representation Learning


Oct 06, 2020
Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang


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Decoder-free Robustness Disentanglement without (Additional) Supervision


Jul 02, 2020
Yifei Wang, Dan Peng, Furui Liu, Zhenguo Li, Zhitang Chen, Jiansheng Yang


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Low Rank Directed Acyclic Graphs and Causal Structure Learning


Jun 10, 2020
Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He


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Clustering Causal Additive Noise Models


Jun 08, 2020
Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng


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CausalVAE: Structured Causal Disentanglement in Variational Autoencoder


Apr 18, 2020
Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang


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A Graph Autoencoder Approach to Causal Structure Learning


Nov 18, 2019
Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang

* NeurIPS 2019 Workshop "Do the right thing": machine learning and causal inference for improved decision making 

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Masked Gradient-Based Causal Structure Learning


Oct 18, 2019
Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen


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Causal Discovery by Kernel Intrinsic Invariance Measure


Sep 02, 2019
Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse

* 9 pages, preprint 

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Asymptotically Optimal One- and Two-Sample Testing with Kernels


Aug 27, 2019
Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang

* Submitted to IEEE Transactions on Information Theory. Short conference version can be found at arXiv:1802.07581 

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Domain Generalization via Multidomain Discriminant Analysis


Jul 25, 2019
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan

* UAI 2019 

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Causal Discovery with Reinforcement Learning


Jun 11, 2019
Shengyu Zhu, Zhitang Chen

* 10 pages, preprint 

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Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration


Nov 27, 2018
Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu


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Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models


Oct 27, 2018
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng

* Published at NIPS 2018 

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A Kernel Embedding-based Approach for Nonstationary Causal Model Inference


Sep 23, 2018
Shoubo Hu, Zhitang Chen, Laiwan Chan

* Neural computation, 30(5), 1394-1425, 2018 
* Published at Neural Computation 

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Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning


Jun 05, 2018
Thomas G. Dietterich, George Trimponias, Zhitang Chen

* To appear at ICML 2018 

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Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit


May 26, 2018
Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen

* 12 pages 

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Exponentially Consistent Kernel Two-Sample Tests


May 21, 2018
Shengyu Zhu, Biao Chen, Zhitang Chen

* 17 pages. Added application to off-line change detection 

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