Meta-Learning with Adjoint Methods
Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe

AISTATS 2023

arXiv | code 

Infinite-Fidelity Coregionalization for Physical Simulation
Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe

NeurIPS 2022

paper | code | video | bib

 
      @inproceedings{
      li2022infinitefidelity,
      title={Infinite-Fidelity Coregionalization  for Physical Simulation},
      author={Shibo Li and Zheng Wang and Robert Kirby and Shandian Zhe},
      booktitle={Advances in Neural Information Processing Systems},
      editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
      year={2022},
      url={https://openreview.net/forum?id=dUYLikScE-}
      }
      

Batch Multi-Fidelity Active Learning with Budget Constraints
Shibo Li*, Jeff Phillips*, Xin Yu, Robert M. Kirby, and Shandian Zhe

NeurIPS 2022

paper | code | video | bib

 
      @inproceedings{
      li2022batch,
      title={Batch Multi-Fidelity Active Learning with Budget Constraints},
      author={Shibo Li and Jeff Phillips and Xin Yu and Robert Kirby and Shandian Zhe},
      booktitle={Advances in Neural Information Processing Systems},
      editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
      year={2022},
      url={https://openreview.net/forum?id=MNQMy2MpbcO}
      }
      

Decomposing Temporal High-Order Interactions via Latent ODEs
Shibo Li, Mike Kirby, Shandian Zhe

ICML 2022

paper | code | video | bib

 
      @InProceedings{pmlr-v162-li22i,
        title =    {Decomposing Temporal High-Order Interactions via Latent {ODE}s},
        author =       {Li, Shibo and Kirby, Robert and Zhe, Shandian},
        booktitle =    {Proceedings of the 39th International Conference on Machine Learning},
        pages =    {12797--12812},
        year =   {2022},
        editor =   {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
        volume =   {162},
        series =   {Proceedings of Machine Learning Research},
        month =    {17--23 Jul},
        publisher =    {PMLR},
        pdf =    {https://proceedings.mlr.press/v162/li22i/li22i.pdf},
        url =    {https://proceedings.mlr.press/v162/li22i.html},
      }
      

Nonparametric Embeddings of Sparse High-Order Interaction Events
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe

ICML 2022

paper | code | video | bib

 
      @InProceedings{pmlr-v162-wang22ah,
        title =    {Nonparametric Embeddings of Sparse High-Order Interaction Events},
        author =       {Wang, Zheng and Xu, Yiming and Tillinghast, Conor and Li, Shibo and Narayan, Akil and Zhe, Shandian},
        booktitle =    {Proceedings of the 39th International Conference on Machine Learning},
        pages =    {23237--23253},
        year =   {2022},
        editor =   {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
        volume =   {162},
        series =   {Proceedings of Machine Learning Research},
        month =    {17--23 Jul},
        publisher =    {PMLR},
        pdf =    {https://proceedings.mlr.press/v162/wang22ah/wang22ah.pdf},
        url =    {https://proceedings.mlr.press/v162/wang22ah.html},
      }
      

Deep Multi-Fidelity Active Learning of High-Dimensional Outputs
Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe

AISTATS 2022

arXiv | code | video | bib

 
      @InProceedings{pmlr-v151-li22b,
        title =    { Deep Multi-Fidelity Active Learning of High-Dimensional Outputs },
        author =       {Li, Shibo and Wang, Zheng and Kirby, Robert and Zhe, Shandian},
        booktitle =    {Proceedings of The 25th International Conference on Artificial Intelligence and Statistics},
        pages =    {1694--1711},
        year =   {2022},
        editor =   {Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel},
        volume =   {151},
        series =   {Proceedings of Machine Learning Research},
        month =    {28--30 Mar},
        publisher =    {PMLR},
        pdf =    {https://proceedings.mlr.press/v151/li22b/li22b.pdf},
        url =    {https://proceedings.mlr.press/v151/li22b.html},
      }

Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
Shibo Li, Mike Kirby, Shandian Zhe

NeurIPS 2021

arXiv | code | video | bib

 @article{li2021batch,
      title={Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks},
      author={Li, Shibo and Kirby, Robert and Zhe, Shandian},
      journal={Advances in Neural Information Processing Systems},
      volume={34},
      pages={25463--25475},
      year={2021}
    }

Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe

NeurIPS 2020

arXiv | code | supplementary | video | bib

  @article{li2020multi,
        title={Multi-fidelity Bayesian optimization via deep neural networks},
        author={Li, Shibo and Xing, Wei and Kirby, Robert and Zhe, Shandian},
        journal={Advances in Neural Information Processing Systems},
        volume={33},
        pages={8521--8531},
        year={2020}
      }

Scalable Variational Gaussian Process Regression Networks
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe

IJCAI 2020

arXiv | code | video | bib

  @inproceedings{ijcai2020p340,
        title     = {Scalable Gaussian Process Regression Networks},
        author    = {Li, Shibo and Xing, Wei and Kirby, Robert M. and Zhe, Shandian},
        booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
                     Artificial Intelligence, {IJCAI-20}},
        publisher = {International Joint Conferences on Artificial Intelligence Organization},
        editor    = {Christian Bessiere},
        pages     = {2456--2462},
        year      = {2020},
        month     = {7},
        note      = {Main track},
        doi       = {10.24963/ijcai.2020/340},
        url       = {https://doi.org/10.24963/ijcai.2020/340},
      }
      }

Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank
Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai

CIKM 2020

arXiv | bib

  @inproceedings{yang2020analysis,
        title={Analysis of multivariate scoring functions for automatic unbiased learning to rank},
        author={Yang, Tao and Fang, Shikai and Li, Shibo and Wang, Yulan and Ai, Qingyao},
        booktitle={Proceedings of the 29th ACM International Conference on Information \& Knowledge Management},
        pages={2277--2280},
        year={2020}
      }