Lu, Xiuyuan

12 publications

ECCV 2024 Event-Aided Time-to-Collision Estimation for Autonomous Driving Jinghang Li, Bangyan Liao, Xiuyuan Lu, Peidong Liu, Shaojie Shen, Yi Zhou

ICMLW 2024 RLHF and IIA: Perverse Incentives Wanqiao Xu, Shi Dong, Xiuyuan Lu, Grace Lam, Zheng Wen, Benjamin Van Roy

UAI 2023 Approximate Thompson Sampling via Epistemic Neural Networks Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

TMLR 2023 Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy

NeurIPS 2023 Epistemic Neural Networks Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy

FnTML 2023 Reinforcement Learning, Bit by Bit Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen

NeurIPS 2022 An Analysis of Ensemble Sampling Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy

UAI 2022 Evaluating High-Order Predictive Distributions in Deep Learning Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy

NeurIPS 2022 The Neural Testbed: Evaluating Joint Predictions Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy

ICLR 2020 Hypermodels for Exploration Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy

NeurIPS 2019 Information-Theoretic Confidence Bounds for Reinforcement Learning Xiuyuan Lu, Benjamin Van Roy

NeurIPS 2017 Ensemble Sampling Xiuyuan Lu, Benjamin Van Roy