Ensemble Sampling. - Xiuyuan Lu; Benjamin Van Roy (NIPS, 2017)

Efficient online recommendation via low-rank ensemble sampling. - Xiuyuan Lu; Zheng Wen; Branislav Kveton (RecSys, 2018)

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

Hypermodels for Exploration. - Vikranth Dwaracherla; Xiuyuan Lu; Morteza Ibrahimi; Ian Osband; Zheng Wen 002; Benjamin Van Roy (ICLR, 2020)

Event-based Motion Segmentation by Cascaded Two-Level Multi-Model Fitting. - Xiuyuan Lu; Yi Zhou 010; Shaojie Shen (IROS, 2021)

Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions. - Xiuyuan Lu; Ian Osband; Benjamin Van Roy; Zheng Wen 002 (CoRR, 2021)

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Botao Hao; Morteza Ibrahimi; Dieterich Lawson; Xiuyuan Lu; Brendan O'Donoghue; Benjamin Van Roy (CoRR, 2021)

The Neural Testbed: Evaluating Joint Predictions. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Xiuyuan Lu; Morteza Ibrahimi; Dieterich Lawson; Botao Hao; Brendan O'Donoghue; Benjamin Van Roy (NeurIPS, 2022)

An Analysis of Ensemble Sampling. - Chao Qin; Zheng Wen 002; Xiuyuan Lu; Benjamin Van Roy (NeurIPS, 2022)

Evaluating high-order predictive distributions in deep learning. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Xiuyuan Lu; Benjamin Van Roy (UAI, 2022)

Robustness of Epinets against Distributional Shifts. - Xiuyuan Lu; Ian Osband; Seyed Mohammad Asghari; Sven Gowal; Vikranth Dwaracherla; Zheng Wen 002; Benjamin Van Roy (CoRR, 2022)

GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation. - Shaozu Cao; Xiuyuan Lu; Shaojie Shen (IEEE Trans. Robotics, 2022)

Epistemic Neural Networks. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Morteza Ibrahimi; Xiuyuan Lu; Benjamin Van Roy (NeurIPS, 2023)

Approximate Thompson Sampling via Epistemic Neural Networks. - Ian Osband; Zheng Wen 002; Seyed Mohammad Asghari; Vikranth Dwaracherla; Morteza Ibrahimi; Xiuyuan Lu; Benjamin Van Roy (UAI, 2023)

Event-based Visual Inertial Velometer. - Xiuyuan Lu; Yi Zhou 010; Shaojie Shen (CoRR, 2023)

RLHF and IIA: Perverse Incentives. - Wanqiao Xu; Shi Dong 003; Xiuyuan Lu; Grace Lam; Zheng Wen 002; Benjamin Van Roy (CoRR, 2023)

Reinforcement Learning, Bit by Bit. - Xiuyuan Lu; Benjamin Van Roy; Vikranth Dwaracherla; Morteza Ibrahimi; Ian Osband; Zheng Wen 002 (Found. Trends Mach. Learn., 2023)

Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. - Vikranth Dwaracherla; Zheng Wen 002; Ian Osband; Xiuyuan Lu; Seyed Mohammad Asghari; Benjamin Van Roy (Trans. Mach. Learn. Res., 2023)

Event-Based Motion Segmentation With Spatio-Temporal Graph Cuts. - Yi Zhou 010; Guillermo Gallego 002; Xiuyuan Lu; Siqi Liu; Shaojie Shen (IEEE Trans. Neural Networks Learn. Syst., 2023)

Event-Aided Time-to-Collision Estimation for Autonomous Driving. - Jinghang Li; Bangyan Liao; Xiuyuan Lu; Peidong Liu 001; Shaojie Shen; Yi Zhou 010 (ECCV (54), 2024)

Event-based Visual Inertial Velometer. - Xiuyuan Lu; Yi Zhou 010; Junkai Niu; Sheng Zhong; Shaojie Shen (Robotics: Science and Systems, 2024)

Event-Based Visual-Inertial State Estimation for High-Speed Maneuvers. - Xiuyuan Lu; Yi Zhou 010; Jiayao Mai; Kuan Dai; Yang Xu; Shaojie Shen (IEEE Trans. Robotics, 2025)

ESVO2: Direct Visual-Inertial Odometry With Stereo Event Cameras. - Junkai Niu; Sheng Zhong; Xiuyuan Lu; Shaojie Shen; Guillermo Gallego 002; Yi Zhou 010 (IEEE Trans. Robotics, 2025)