MC-Fluid: Fluid Model-Based Mixed-Criticality Scheduling on Multiprocessors. - Jaewoo Lee; Kieu-My Phan; Xiaozhe Gu; Jiyeon Lee; Arvind Easwaran; Insik Shin; Insup Lee 001 (RTSS, 2014)

Resource Efficient Isolation Mechanisms in Mixed-Criticality Scheduling. - Xiaozhe Gu; Arvind Easwaran; Kieu-My Phan; Insik Shin (ECRTS, 2015)

Dynamic Budget Management with Service Guarantees for Mixed-Criticality Systems. - Xiaozhe Gu; Arvind Easwaran (RTSS, 2016)

Design and Analysis for Dual Priority Scheduling. - Xiaozhe Gu; Arvind Easwaran; Risat Pathan (ISORC, 2018)

Efficient Schedulability Test for Dynamic-Priority Scheduling of Mixed-Criticality Real-Time Systems. - Xiaozhe Gu; Arvind Easwaran (ACM Trans. Embed. Comput. Syst., 2018)

Schedulability analysis and low-criticality execution support for mixed-criticality real-time systems on uniprocessors - Xiaozhe Gu (2018)

Towards safe machine learning for CPS: infer uncertainty from training data. - Xiaozhe Gu; Arvind Easwaran (ICCPS, 2019)

Dynamic budget management and budget reclamation for mixed-criticality systems. - Xiaozhe Gu; Arvind Easwaran (Real Time Syst., 2019)

A Resource-efficient Spiking Neural Network Accelerator Supporting Emerging Neural Encoding. - Daniel Gerlinghoff; Zhehui Wang; Xiaozhe Gu; Rick Siow Mong Goh; Tao Luo 014 (DATE, 2022)

Temperature Annealing Knowledge Distillation from Averaged Teacher. - Xiaozhe Gu; Zixun Zhang; Tao Luo 014 (ICDCS Workshops, 2022)

E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks With Emerging Neural Encoding on FPGAs. - Daniel Gerlinghoff; Zhehui Wang; Xiaozhe Gu; Rick Siow Mong Goh; Tao Luo 014 (IEEE Trans. Parallel Distributed Syst., 2022)

Hierarchical Weight Averaging for Deep Neural Networks. - Xiaozhe Gu; Zixun Zhang; Yuncheng Jiang; Tao Luo 005; Ruimao Zhang; Shuguang Cui; Zhen Li 026 (CoRR, 2023)

Benchmarking Quantum(-Inspired) Annealing Hardware on Practical Use Cases. - Tian Huang; Jun Xu; Tao Luo 014; Xiaozhe Gu; Rick Siow Mong Goh; Weng-Fai Wong (IEEE Trans. Computers, 2023)

Progressively Relaxed Knowledge Distillation. - Xiaozhe Gu; Ran Jin; Mingliang Li (IJCNN, 2024)

Efficient Spiking Neural Networks With Radix Encoding. - Zhehui Wang; Xiaozhe Gu; Rick Siow Mong Goh; Joey Tianyi Zhou; Tao Luo 014 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hierarchical Weight Averaging for Deep Neural Networks. - Xiaozhe Gu; Zixun Zhang; Yuncheng Jiang; Tao Luo 014; Ruimao Zhang; Shuguang Cui; Zhen Li 026 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Self-distillation with model averaging. - Xiaozhe Gu; Zixun Zhang; Ran Jin; Rick Siow Mong Goh; Tao Luo 014 (Inf. Sci., 2025)

EFKAN: A KAN-Integrated Neural Operator For Efficient Magnetotelluric Forward Modeling. - Feng Wang 031; Hong Qiu; Yingying Huang; Xiaozhe Gu; Renfang Wang; Bo Yang 060 (CoRR, 2025)