Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes. - Xubo Yue; Raed Kontar (CoRR, 2019)

The Rényi Gaussian Process. - Xubo Yue; Raed Kontar (CoRR, 2019)

Lookahead Bayesian Optimization via Rollout: Guarantees and Sequential Rolling Horizons. - Xubo Yue; Raed Al Kontar (CoRR, 2019)

Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout. - Xubo Yue; Raed Al Kontar (AISTATS, 2020)

SALR: Sharpness-aware Learning Rates for Improved Generalization. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (CoRR, 2020)

The Internet of Federated Things (IoFT). - Raed Kontar; Naichen Shi; Xubo Yue; Seokhyun Chung; Eunshin Byon; Mosharaf Chowdhury; Jionghua Jin 001; Wissam Kontar; Neda Masoud; Maher Nouiehed; Chinedum Emmanuel Okwudire; Garvesh Raskutti; et al. (IEEE Access, 2021)

GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (CoRR, 2021)

The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning. - Raed Kontar; Naichen Shi; Xubo Yue; Seokhyun Chung; Eunshin Byon; Mosharaf Chowdhury; Judy Jin; Wissam Kontar; Neda Masoud; Maher Nouiehed; Chinedum Emmanuel Okwudire; Garvesh Raskutti; et al. (CoRR, 2021)

Joint Models for Event Prediction From Time Series and Survival Data. - Xubo Yue; Raed Al Kontar (Technometrics, 2021)

Self-scalable Tanh (Stan): Faster Convergence and Better Generalization in Physics-informed Neural Networks. - Raghav Gnanasambandam; Bo Shen 005; Jihoon Chung; Xubo Yue; Zhenyu James Kong (CoRR, 2022)

Federated Data Analytics: A Study on Linear Models. - Xubo Yue; Raed Al Kontar; Ana María Estrada Gómez (CoRR, 2022)

Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design. - Xubo Yue; Raed Al Kontar; Albert S. Berahas; Yang Liu; Zhenghao Zai; Kevin Edgar; Blake N. Johnson (CoRR, 2023)

Self-Scalable Tanh (Stan): Multi-Scale Solutions for Physics-Informed Neural Networks. - Raghav Gnanasambandam; Bo Shen 005; Jihoon Chung; Xubo Yue; Zhenyu James Kong (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning. - Jianhong Chen; Ying Ma; Xubo Yue (CoRR, 2024)

The optimization and operation of multi-energy-coupled microgrids by the improved fireworks algorithm-shuffled frog-leaping algorithm. - Xubo Yue; Jing Zhang; Junhui Guo; Jianfei Li; Diyu Chen (PeerJ Comput. Sci., 2024)

Federated Gaussian Process: Convergence, Automatic Personalization and Multi-Fidelity Modeling. - Xubo Yue; Raed Kontar (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

SALR: Sharpness-Aware Learning Rate Scheduler for Improved Generalization. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (IEEE Trans. Neural Networks Learn. Syst., 2024)

Collaborative and Distributed Bayesian Optimization via Consensus. - Xubo Yue; Yang Liu; Albert S. Berahas; Blake N. Johnson; Raed Al Kontar (IEEE Trans Autom. Sci. Eng., 2025)

Explainable Federated Bayesian Causal Inference and Its Application in Advanced Manufacturing. - Xiaofeng Xiao; Khawlah Alharbi; Pengyu Zhang; Hantang Qin; Xubo Yue (CoRR, 2025)

Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning. - Cheoljoon Jeong; Xubo Yue; Seokhyun Chung (CoRR, 2025)

Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations. - Xiaofeng Xiao; Bo Shen; Xubo Yue (CoRR, 2025)

Toward Temporal Causal Representation Learning with Tensor Decomposition. - Jianhong Chen; Meng Zhao; Mostafa Reisi Gahrooei; Xubo Yue (CoRR, 2025)