Search Results for author: Zijian Guo

Found 15 papers, 7 papers with code

STT: Stateful Tracking with Transformers for Autonomous Driving

no code implementations30 Apr 2024 Longlong Jing, Ruichi Yu, Xu Chen, Zhengli Zhao, Shiwei Sheng, Colin Graber, Qi Chen, Qinru Li, Shangxuan Wu, Han Deng, Sangjin Lee, Chris Sweeney, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, Zijian Guo, Yin Zhou, Mingxing Tan, Weilong Yang, CongCong Li

In this paper, we propose STT, a Stateful Tracking model built with Transformers, that can consistently track objects in the scenes while also predicting their states accurately.

Autonomous Driving

Uniform Inference for Nonlinear Endogenous Treatment Effects with High-Dimensional Covariates

1 code implementation12 Oct 2023 Qingliang Fan, Zijian Guo, Ziwei Mei, Cun-Hui Zhang

In this paper, we propose new estimation and inference procedures for nonparametric treatment effect functions with endogeneity and potentially high-dimensional covariates.

Distributionally Robust Transfer Learning

no code implementations12 Sep 2023 Xin Xiong, Zijian Guo, Tianxi Cai

Many existing transfer learning methods rely on leveraging information from source data that closely resembles the target data.

Transfer Learning

Distributionally Robust Machine Learning with Multi-source Data

no code implementations5 Sep 2023 Zhenyu Wang, Peter Bühlmann, Zijian Guo

Classical machine learning methods may lead to poor prediction performance when the target distribution differs from the source populations.

Federated Learning

Datasets and Benchmarks for Offline Safe Reinforcement Learning

3 code implementations15 Jun 2023 Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao

This paper presents a comprehensive benchmarking suite tailored to offline safe reinforcement learning (RL) challenges, aiming to foster progress in the development and evaluation of safe learning algorithms in both the training and deployment phases.

Autonomous Driving Benchmarking +4

On the Robustness of Safe Reinforcement Learning under Observational Perturbations

1 code implementation29 May 2022 Zuxin Liu, Zijian Guo, Zhepeng Cen, huan zhang, Jie Tan, Bo Li, Ding Zhao

One interesting and counter-intuitive finding is that the maximum reward attack is strong, as it can both induce unsafe behaviors and make the attack stealthy by maintaining the reward.

Adversarial Attack reinforcement-learning +2

A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates

1 code implementation30 Apr 2022 Qingliang Fan, Zijian Guo, Ziwei Mei

The novelty of the proposed test is that it allows the number of covariates and instruments to be larger than the sample size.

Vocal Bursts Intensity Prediction

Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction

no code implementations4 May 2021 Jue Hou, Zijian Guo, Tianxi Cai

Risk modeling with EHR data is challenging due to a lack of direct observations on the disease outcome, and the high dimensionality of the candidate predictors.

Genetic Risk Prediction Imputation +2

Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding

1 code implementation8 Apr 2020 Zijian Guo, Domagoj Ćevid, Peter Bühlmann

Inferring causal relationships or related associations from observational data can be invalidated by the existence of hidden confounding.

Methodology Statistics Theory Statistics Theory

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