Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap
Weiyang Liu*, Longhui Yu*, Adrian Weller, Bernhard Schölkopf

ICLR 2023

arXiv | code | openreview | bib

  @article{Liu2023HUG,
      title={Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap},
      author={Liu, Weiyang and Yu, Longhui and Weller, Adrian and Schölkopf, Bernhard},
      booktitle = {ICLR},
      year={2023}}

Score-based Generative 3D Mesh Modeling
Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu

ICLR 2023   Spotlight

arXiv | code | openreview | bib

  @article{Liu2023MeshDiffusion,
      title={Score-based Generative 3D Mesh Modeling},
      author={Liu, Zhen and Feng, Yao and Black, Michael J. and Nowrouzezahrai, Derek 
        and Paull, Liam and Liu, Weiyang},
      booktitle = {ICLR},
      year={2023}}

Iterative Teaching by Data Hallucination
Zeju Qiu*, Weiyang Liu*, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf

AISTATS 2023

arXiv | code | bib

  @article{Qiu2023DHT,
      title={Iterative Teaching by Data Hallucination},
      author={Qiu, Zeju and Liu, Weiyang and Xiao, Tim Z and Liu, Zhen 
        and Bhatt, Umang and Luo, Yucen and Weller, Adrian and Schölkopf, Bernhard},
      booktitle = {AISTATS},
      year={2023}}

Continual Learning by Modeling Intra-Class Variation
Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu

TMLR 2023

arXiv | code | openreview | bib

  @article{Yu2022MOCA,
      title={Continual Learning by Modeling Intra-Class Variation},
      author={Yu, Longhui and Hu, Tianyang and Hong, Lanqing and Liu, Zhen and Weller, Adrian and Liu, Weiayng},
      journal = {arXiv preprint arXiv:2210.05398},
      year={2022}}

Structural Causal 3D Reconstruction
Weiyang Liu*, Zhen Liu*, Liam Paull, Adrian Weller, Bernhard Schölkopf

ECCV 2022

arXiv | code | talk | slides | bib

  @InProceedings{Liu2022SCR,
      title={Structural Causal 3D Reconstruction},
      author={Liu, Weiyang and Liu, Zhen and Paull, Liam and Weller, Adrian and Schölkopf, Bernhard},
      booktitle = {ECCV},
      year={2022}}

Towards Principled Disentanglement for Domain Generalization
Hanlin Zhang*, Yi-Fan Zhang*, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric Xing

CVPR 2022   Oral

arXiv | code | talk | bib

  @InProceedings{Zhang2022DDG,
      title={Towards Principled Disentanglement for Domain Generalization},
      author={Zhang, Hanlin and Zhang, Yi-Fan and Liu, Weiyang and Weller, Adrian and Sch{\"o}lkopf, Bernhard and Xing, Eric P},
      booktitle = {CVPR},
      year={2022}}

SphereFace Revived: Unifying Hyperspherical Face Recognition
Weiyang Liu*, Yandong Wen*, Bhiksha Raj, Rita Singh, Adrian Weller

TPAMI 2022

arXiv | code | opensphere | IEEE Xplore | bib

  @article{Liu2022SphereFaceR,
      title={SphereFace Revived: Unifying Hyperspherical Face Recognition},
      author={Liu, Weiyang and Wen, Yandong and Raj, Bhiksha and Singh, Rita and Weller, Adrian},
      journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
      year={2022}}

SphereFace2: Binary Classification is All You Need for Deep Face Recognition
Yandong Wen*, Weiyang Liu*, Adrian Weller, Bhiksha Raj, Rita Singh

ICLR 2022   Spotlight

arXiv | code | project | openreview | slides | bib

  @InProceedings{Wen2021SphereFace2,
      title={SphereFace2: Binary Classification is All You Need for Deep Face Recognition},
      author={Wen, Yandong and Liu, Weiyang and Weller, Adrian and Raj, Bhiksha and Singh, Rita},
      booktitle = {ICLR},
      year={2022}}

Pre-training Molecular Graph Representation with 3D Geometry
Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

ICLR 2022

arXiv | code | project | openreview | talk | slides | bib

  @InProceedings{Liu2021GraphMVP,
      title={Pre-training Molecular Graph Representation with 3D Geometry},
      author={Liu, Shengchao and Wang, Hanchen and Liu, Weiyang and Lasenby, Joan and Guo, Hongyu and Tang, Jian},
      booktitle={ICLR},
      year={2022}}

Provable Lifelong Learning of Representations
Xinyuan Cao*, Weiyang Liu*, Santosh S. Vempala*

AISTATS 2022

arXiv | talk | slides | bib

  @InProceedings{Cao2021LLL,
      title={Provable Lifelong Learning of Representations},
      author={Cao, Xinyuan and Liu, Weiyang and Vempala, Santosh S},
      booktitle = {AISTATS},
      year={2022}}

Iterative Teaching by Label Synthesis
Weiyang Liu*, Zhen Liu*, Hanchen Wang*, Liam Paull, Bernhard Schölkopf, Adrian Weller

NeurIPS 2021   Spotlight

arXiv | code | openreview | talk | slides | video | bib

  @InProceedings{Liu2021LAST,
      title={Iterative Teaching by Label Synthesis},
      author={Liu, Weiyang and Liu, Zhen and Wang, Hanchen and Paull, Liam and Schölkopf, Bernhard and Weller, Adrian},
      booktitle = {NeurIPS},
      year={2021}}

Locality Sensitive Teaching
Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin, Anshumali Shrivastava

NeurIPS 2021

arXiv | code | openreview | talk | slides | bib

  @InProceedings{Xu2021LST,
      title={Locality Sensitive Teaching},
      author={Xu, Zhaozhuo and Chen, Beidi and Li, Chaojian and Liu, Weiyang and Song, Le and Lin, Yingyan and Shrivastava, Anshumali},
      booktitle = {NeurIPS},
      year={2021}}

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Xiang Bai, Hanchen Wang, ..., Weiyang Liu, ..., Carola Schönlieb, Tian Xia

Nature Machine Intelligence 2021

arXiv | code | project | news | bib

  @article{UCADI2021NMI,
      title={Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence},
      author={Bai, Xiang and Wang, Hanchen and Ma, Liya and Xu, Yongchao and Gan, Jiefeng and Fan, Ziwei and Yang, Fan and Ma, Ke and Yang, Jiehua and Bai, Song and others},
      journal={Nature Machine Intelligence},
      volume={3},
      number={12},
      pages={1081--1089},
      year={2021},
      publisher={Nature Publishing Group}}

Self-Supervised 3D Face Reconstruction via Conditional Estimation
Yandong Wen, Weiyang Liu, Bhiksha Raj, Rita Singh

ICCV 2021

arXiv | code | talk | poster | bib

  @InProceedings{Wen2021CEST,
      title={Self-Supervised 3D Face Reconstruction via Conditional Estimation},
      author={Wen, Yandong and Liu, Weiyang and Raj, Bhiksha and Singh, Rita},
      booktitle={ICCV},
      year={2021}}

Learning with Hyperspherical Uniformity
Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller

AISTATS 2021

arXiv | code | talk | slides | bib

  @InProceedings{Liu2021SphereUni,
      title={Learning with Hyperspherical Uniformity},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Xiong, Li and Schölkopf, Bernhard and Weller, Adrian},
      booktitle={AISTATS},
      year={2021}}

Orthogonal Over-Parameterized Training
Weiyang Liu*, Rongmei Lin*, Zhen Liu, James Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller

CVPR 2021   Oral

arXiv | code | project | talk | slides | bib

  @InProceedings{Liu2021OPT,
      title={Orthogonal Over-Parameterized Training},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Rehg, James M. and Paull, Liam 
       and Xiong, Li and Song, Le and Weller, Adrian},
      booktitle={CVPR},
      year={2021}}

Angular Visual Hardness
Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar

ICML 2020

arXiv | code | project | talk | long talk | slides | bib

  @InProceedings{Chen20AVH,
      title={Angular Visual Hardness},
      author={Chen, Beidi and Liu, Weiyang and Garg, Animesh and Yu, Zhiding 
       and Shrivastava, Anshumali and Anandkumar, Animashree},
      booktitle={ICML},
      year={2020}}

Regularizing Neural Networks via Minimizing Hyperspherical Energy
Rongmei Lin, Weiyang Liu*, Zhen Liu, Chen Feng, Zhiding Yu, James Rehg, Li Xiong, Le Song

CVPR 2020

arXiv | code | talk | slides | bib

  @InProceedings{Lin20CoMHE,
      title={Regularizing Neural Networks via Minimizing Hyperspherical Energy},
      author={Lin, Rongmei and Liu, Weiyang and Liu, Zhen and Feng, Chen and Yu, Zhiding 
       and Rehg, James M. and Xiong, Li and Song, Le},
      booktitle={CVPR},
      year={2020}}

Neural Similarity Learning
Weiyang Liu, Zhen Liu, James Rehg, Le Song

NeurIPS 2019

arXiv | code | talk | slides | bib

  @InProceedings{LiuNIPS19,
      title={Neural Similarity Learning},
      author={Liu, Weiyang and Liu, Zhen and Rehg, James and Song, Le},
      booktitle={NeurIPS},
      year={2019}}

Meta Architecture Search
Albert Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai

NeurIPS 2019

arXiv | code | poster | bib

  @InProceedings{ShawNIPS19,
      title={Meta Architecture Search},
      author={Shaw, Albert and Wei, Wei and Liu, Weiyang and Song, Le and Dai, Bo},
      booktitle={NeurIPS},
      year={2019}}

Disjoint Mapping Network for Cross-modal Matching of Voices and Faces
Yandong Wen, Mahmoud Alismail, Weiyang Liu, Bhiksha Raj, Rita Singh

ICLR 2019

arXiv | code | openreview | poster | bib

  @InProceedings{Wen2019DIM,
      title={Disjoint Mapping Network for Cross-modal Matching of Voices and Faces},
      author={Wen, Yandong and Alismail, Mahmoud and Liu, Weiyang and Raj, Bhiksha and Singh, Rita},
      booktitle={ICLR},
      year={2019}}

Coupled Variational Bayes via Optimization Embedding
Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

NeurIPS 2018

arXiv | code | poster | bib

  @InProceedings{DaiNIPS18,
      title={Coupled Variational Bayes via Optimization Embedding},
      author={Dai, Bo and Dai, Hanjun and He, Niao and Liu, Weiyang 
       and Liu, Zhen and Chen, Jianshu and Xiao, Lin and Song, Le},
      booktitle={NeurIPS},
      year={2018}}

Simultaneous Edge Alignment and Learning
Zhiding Yu, Weiyang Liu, Yang Zou, Chen Feng, Srikumar Ramalingam, Vijaya Kumar, Jan Kautz

ECCV 2018

arXiv | code | project | demo | slides | bib

  @article{YuECCV18,
      title={Simultaneous Edge Alignment and Learning},
      author={Yu, Zhiding and Liu, Weiyang and Zou, Yang and Feng, Chen
       and Ramalingam, Srikumar and Kumar, Vijaya and Kautz, Jan},
      journal={arXiv preprint arXiv:1807.04836},
      year={2018}}

Towards Black-box Iterative Machine Teaching
Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, Le Song

ICML 2018    

arXiv | talk | slides | bib

  @InProceedings{Liu2018ICML,
      author={Liu, Weiyang and Dai, Bo and Li, Xingguo and Rehg, James M and Song, Le},
      title = {Towards Black-box Iterative Machine Teaching},
      booktitle = {ICML},
      year = {2018}}

Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia

CVPR 2018   Spotlight

arXiv | code | slides | bib

  @InProceedings{Wang2018ONL,
      author={Wang, Yisen and Liu, Weiyang and Ma, Xingjun and Bailey, James
       and Zha, Hongyuan and Song, Le and Xia, Shu-Tao},
      title={Iterative Learning with Open-set Noisy Labels},
      booktitle = {CVPR},
      year = {2018}}

Additive Margin Softmax for Face Verification
Feng Wang, Weiyang Liu, Haijun Liu, Jian Cheng

ICLR 2018   Workshop   Most Popular Paper

arXiv | code | openreview | journal | bib

  @article{Wang2018ICLRW,
      title = {Additive Margin Softmax for Face Verification},
      author = {Wang, Feng and Liu, Weiyang and Liu, Haijun and Cheng, Jian},
      journal = {arXiv preprint arXiv:1801.05599},
      year = {2018}}