Chen Xu's Personal Webpage

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I am an incoming Research Scientist in the Large Behavior Modeling (LBM) team at Toyota Research Institute. I completed my PhD under the supervision of Prof. Yao Xie at Georgia Tech. Before my PhD, I completed my joint BS/MS degree from the University of Chicago, where my MS thesis advisor is Prof. Rina Foygel Barber.

[LinkedIn, Google Scholar, GitHub]

Research Interests: flow-based generative modeling, safe & reliable machine learning.

Research

Flow-based Generative Modeling

  1. Chen Xu, Xiuyuan Cheng, and Yao Xie. Local flow matching generative models. arXiv:2410.02548, 2024.
  2. Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, and Yao Xie. Flow-based distributionally robust optimization. IEEE Journal on Selected Areas in Information Theory (JSAIT), 2024.
  3. Chen Xu, Xiuyuan Cheng, and Yao Xie. Normalizing flow neural networks by jko scheme. NeurIPS 2023 (Spotlight).
  4. Chen Xu, Xiuyuan Cheng, and Yao Xie. Computing high-dimensional optimal transport by flow neural networks. NeurIPS 2023 Workshop Optimal Transport and Machine Learning.
  5. Chen Xu, Xiuyuan Cheng, and Yao Xie. Invertible neural networks for graph prediction. IEEE Journal on Selected Areas in Information Theory (JSAIT), 2022.

Safe & Reliable Machine Learning

  1. Chen Xu, T. K. Nguyen, P. Miller, R. Lee, P. Shah, R. A. Ambrus, H. Nishimura, and M. Itkina. Uncertainty-Aware Failure Detection for Imitation Learning Robot Policies. CoRL 2024 Workshop on Safe and Robust Robot Learning for Operation in the Real World.
  2. Junghwan Lee, Chen Xu, and Yao Xie. Transformer Conformal Prediction for Time Series. ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling.
  3. Jonghyeok Lee, Chen Xu, and Yao Xie. Kernel-based optimally weighted conformal prediction intervals. arXiv:2405.16828, 2024
  4. Chen Xu, Hanyang Jiang, and Yao Xie. Conformal prediction for multi-dimensional time series by ellipsoidal sets. ICML 2024 (Spotlight).
  5. Chen Xu and Yao Xie. Sequential predictive conformal inference for time series. ICML 2023.
  6. Chen Xu and Yao Xie. Conformal prediction for time series. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  7. Chen Xu and Yao Xie. Conformal prediction set for time-series. ICML 2022 Workshop on Distribution-free Uncertainty Quantification.
  8. Chen Xu and Yao Xie. Conformal anomaly detection on spatio-temporal observations with missing data. ICML 2021 Workshop on Distribution-free Uncertainty Quantification.
  9. Chen Xu and Yao Xie. Conformal prediction interval for dynamic time-series. ICML 2021 (oral).
  10. Byol Kim, Chen Xu, and Rina Barber. Predictive inference is free with the jackknife+-after-bootstrap. NeurIPS 2020.

Miscellaneous

  1. Minghe Zhang, Chen Xu, Andy Sun, Feng Qiu, and Yao Xie. Solar radiation ramping events modeling using spatio-temporal point processes. (Minor revision) INFORMS Journal on Data Science, 2024.
  2. Chen Xu, Yao Xie, Daniel A Zuniga Vazquez, Rui Yao, and Feng Qiu. Spatio-temporal wildfire prediction using multi-modal data. IEEE Journal on Selected Areas in Information Theory (JSAIT), 2023.
  3. Anatoli Juditsky, Arkadi Nemirovski, Yao Xie, and Chen Xu. Generalized generalized linear models: Convex estimation and online bounds. arXiv:2304.13793, 2023.
  4. Chen Xu, Xiuyuan Cheng, and Yao Xie. An alternative approach to train neural networks using monotone variational inequality. OPT 2023: Optimization for Machine Learning.