Research Projects

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Relationship of Data Complexity and Model Robustness

Peking University; Advisor: Prof. Zhanxing Zhu; Oct. 2018-present

Did a paper review on theoretical analysis about network robustness and generalizability.
Experimentally discovered the relationship between robustness and data amount and input dimension.
Tried introducing randomness into network weights and feature maps to improve robustness.

Defense of Adversarial Examples vis Sparse Coding [Arxiv]

UCSD; Advisor: Prof. Hao Su; Jul. 2018-Sept.2018

Proposed patch-based Introspective Neural Network for restoration of adversarial examples on ImageNet.
Proposed an attack-agnostic adversarial defense via convolutional sparse coding and outperformed state-of-the-art by up to 26.6%.
Organized and finished an academic paper from scratch.

3D Multi-view Point Cloud Reconstruction from Single Image [AAAI 2019 Oral, pdf]

MSRA; Advisor: Jinglu Wang; Dec. 2017-Mar. 2018

Proposed a 2D convolution-favored 3D point cloud representation recording coordinates and visibilities.
Proposed a post-processing network to refine conversion from point cloud to voxel achieving about 5% IoU shift.
Implemented multi-view point regression network which outperformed state-of-the-art by 0.1 IoU on hard classes.

3D Indoor Scene Reconstruction

MSRA; Advisor: Jinglu Wang; Mar. 2018-May 2018

Reimplemented Roomnet, a proprietary architecture for room key-point detection.
Proposed multi-channel boundary map denoting neighboring and vertical relationships in room plane reconstruction.

Selected Presentations

Neural Process [slide]

Prof. Hao Su's Lab; UCSD

This pre first reviews Gaussian Processes and Variational Auto-encoder. Then it introduces a graph model family - neural processes.

Network Uncertainty [slide]

Prof. Hao Su's Lab; UCSD

This pre introduces two papers related to network uncertainty. The first is Bayesian approximating through dropout. The second is measuring uncertainty for adversarial examples.

Testing Bayesian Network [slide]

Prof. Adnan Darwiche's Lab; UCLA

This pre summarizes Testing Bayesian Network(TBN) which compile Bayesian network queries to arithmetic circuit. Then it posts some discussion and potential applications of TBN.

Network Visualization and Interpretation [slide]

Prof. Yizhou Wang's Lab; PKU

This pre first classifies network visualization and interpretation. Then it introduces several works for every type of method.

Style Transfer [slide]

Prof. Yizhou Wang's Lab; PKU

This pre introduces concept, basic method and several improvements of style transfer.

Generative Adversarial Networks [slide]

Prof. Yizhou Wang's Lab; PKU

This pre introduces the background, method, applications and discussion of generative adversarial networks(GAN).

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