(*) denotes equal contribution.

Preprints

Sampling with Mirrored Stein Operators

Jiaxin Shi, Chang Liu, Lester Mackey.

2021. [pdf] [arxiv] [code]

Conference Papers

Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition

Shengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger Grosse.

ICML, 2021. [pdf] [arxiv] [code]

Nonparametric Score Estimators

Yuhao Zhou, Jiaxin Shi, Jun Zhu.

ICML, 2020. [pdf] [arxiv] [code] [slides]

Sparse Orthogonal Variational Inference for Gaussian Processes

Jiaxin Shi, Michalis K. Titsias, Andriy Mnih.

AISTATS, 2020. [pdf] [arxiv] [code] [slides]

Best Student Paper Runner-Up at AABI, 2019.

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

Yang Song*, Sahaj Garg*, Jiaxin Shi, Stefano Ermon.

UAI, 2019. [pdf] [arxiv] [code] [video] [blog]

Scalable Training of Inference Networks for Gaussian-Process Models

Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu.

ICML, 2019. [pdf] [arxiv] [code] [slides]

Functional Variational Bayesian Neural Networks

Shengyang Sun*, Guodong Zhang*, Jiaxin Shi*, Roger Grosse.

ICLR, 2019. [pdf] [arxiv] [code] [video]

Preliminary version presented at NeurIPS BDL Workshop, 2018.

Semi-crowdsourced Clustering with Deep Generative Models

Yucen Luo, Tian Tian, Jiaxin Shi, Jun Zhu, Bo Zhang.

NeurIPS, 2018. [pdf] [arxiv] [code]

Preliminary version presented at ICML TADGM Workshop, 2018.

A Spectral Approach to Gradient Estimation for Implicit Distributions

Jiaxin Shi, Shengyang Sun, Jun Zhu.

ICML, 2018. [pdf] [arxiv] [code] [slides]

Message Passing Stein Variational Gradient Descent

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

ICML, 2018. [pdf] [arxiv]

Kernel Implicit Variational Inference

Jiaxin Shi*, Shengyang Sun*, Jun Zhu.

ICLR, 2018. [pdf] [arxiv]

Preliminary version presented at ICML Workshop on Implicit Models, 2017.

Other Abstracts

Neural Networks as Inter-domain Inducing Points

Shengyang Sun*, Jiaxin Shi*, Roger Grosse. [pdf] [slides] [video]

Symposium on Advances in Approximate Bayesian Inference, 2020.

Spectral Estimators for Gradient Fields of Log-Densities

Yuhao Zhou, Jiaxin Shi, Jun Zhu.

ICML Workshop on Stein’s Method, 2019.

Visualization & Graphics

Analyzing the Training Processes of Deep Generative Models

Mengchen Liu, Jiaxin Shi, Kelei Cao, Jun Zhu, Shixia Liu.

TVCG, 2018. [pdf]

Towards Better Analysis of Deep Convolutional Neural Networks

Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu.

TVCG, 2017. [pdf]

Most cited paper of TVCG in 2017.

Plenopatch: Patch-based Plenoptic Image Manipulation

Fanglue Zhang, Jue Wang, Eli Shechtman, Ziye Zhou, Jiaxin Shi, Shimin Hu.

TVCG, 2017. [paper]