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Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition


Jun 10, 2021
Shengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger Grosse

* ICML2021, 21 pages 

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TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph


Apr 15, 2021
Jiaxin Shi, Shulin Cao, Lei Hou, Juanzi Li, Hanwang Zhang


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KQA Pro: A Large Diagnostic Dataset for Complex Question Answering over Knowledge Base


Jul 08, 2020
Jiaxin Shi, Shulin Cao, Liangming Pan, Yutong Xiang, Lei Hou, Juanzi Li, Hanwang Zhang, Bin He


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Nonparametric Score Estimators


May 20, 2020
Yuhao Zhou, Jiaxin Shi, Jun Zhu


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Unbiased Scene Graph Generation from Biased Training


Mar 11, 2020
Kaihua Tang, Yulei Niu, Jianqiang Huang, Jiaxin Shi, Hanwang Zhang

* This paper is accepted by CVPR 2020. The code is publicly available on GitHub: https://github.com/KaihuaTang/Scene-Graph-Benchmark.pytorch 

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Sparse Orthogonal Variational Inference for Gaussian Processes


Oct 24, 2019
Jiaxin Shi, Michalis K. Titsias, Andriy Mnih


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Scalable Training of Inference Networks for Gaussian-Process Models


May 27, 2019
Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu

* ICML 2019. Update results added in the camera-ready version 

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Sliced Score Matching: A Scalable Approach to Density and Score Estimation


May 17, 2019
Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon

* UAI 2019 

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Functional Variational Bayesian Neural Networks


Mar 14, 2019
Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger Grosse

* ICLR 2019 

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Explainable and Explicit Visual Reasoning over Scene Graphs


Dec 05, 2018
Jiaxin Shi, Hanwang Zhang, Juanzi Li


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Learning to Embed Sentences Using Attentive Recursive Trees


Nov 15, 2018
Jiaxin Shi, Lei Hou, Juanzi Li, Zhiyuan Liu, Hanwang Zhang

* AAAI Conference of Artificial Intelligence, 2019 

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DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization


Nov 07, 2018
Jiaxin Shi, Chen Liang, Lei Hou, Juanzi Li, Zhiyuan Liu, Hanwang Zhang

* AAAI-19 

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Semi-crowdsourced Clustering with Deep Generative Models


Oct 29, 2018
Yucen Luo, Tian Tian, Jiaxin Shi, Jun Zhu, Bo Zhang

* 32nd Conference on Neural Information Processing Systems (NIPS 2018) 

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Message Passing Stein Variational Gradient Descent


Jun 08, 2018
Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang

* To appear in the Proceedings of the 35th International Conference on Machine Learning (ICML 2018) 

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A Spectral Approach to Gradient Estimation for Implicit Distributions


Jun 07, 2018
Jiaxin Shi, Shengyang Sun, Jun Zhu

* To appear at ICML 2018 

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Kernel Implicit Variational Inference


Feb 23, 2018
Jiaxin Shi, Shengyang Sun, Jun Zhu

* Published as a conference paper at ICLR 2018 

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ZhuSuan: A Library for Bayesian Deep Learning


Sep 18, 2017
Jiaxin Shi, Jianfei Chen, Jun Zhu, Shengyang Sun, Yucen Luo, Yihong Gu, Yuhao Zhou

* The GitHub page is at https://github.com/thu-ml/zhusuan 

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Towards Better Analysis of Deep Convolutional Neural Networks


May 04, 2016
Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu

* Submitted to VIS 2016 

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Building Memory with Concept Learning Capabilities from Large-scale Knowledge Base


Dec 03, 2015
Jiaxin Shi, Jun Zhu

* Accepted to NIPS 2015 Cognitive Computation workshop ([email protected] 2015) 

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