Histopathologic Cancer Detection Based on Deep Multiple Instance Learning. - Meijuan Jia; Xiankun Yan; Shuang Fu (MSN, 2019)

A Novel Adaptive Fuzzy Deep Learning Approach for Histopathologic Cancer Detection. - Xiankun Yan; Jianrui Ding; Heng-Da Cheng (EMBC, 2021)

Runtime Analysis of Simple Evolutionary Algorithms for the Chance-Constrained Makespan Scheduling Problem. - Feng Shi 003; Xiankun Yan; Frank Neumann 001 (PPSN (2), 2022)

Runtime Performance of Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem. - Feng Shi 003; Xiankun Yan; Frank Neumann 001 (CoRR, 2022)

Optimizing Chance-Constrained Submodular Problems with Variable Uncertainties. - Xiankun Yan; Anh Viet Do; Feng Shi 003; Xiaoyu Qin; Frank Neumann 001 (ECAI, 2023)

Finding Antimagic Labelings of Trees by Evolutionary Search. - Luke Branson; Andrew M. Sutton; Xiankun Yan (FOGA, 2023)

Diversity Optimization for the Detection and Concealment of Spatially Defined Communication Networks. - Aneta Neumann; Sharlotte Gounder; Xiankun Yan; Gregory Sherman; Benjamin Campbell; Mingyu Guo; Frank Neumann 001 (GECCO, 2023)

Sampling-based Pareto Optimization for Chance-constrained Monotone Submodular Problems. - Xiankun Yan; Aneta Neumann; Frank Neumann 001 (GECCO, 2024)

Sliding Window Bi-objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions. - Xiankun Yan; Aneta Neumann; Frank Neumann 001 (PPSN (1), 2024)

Runtime performance of evolutionary algorithms for the chance-constrained makespan scheduling problem. - Feng Shi 003; Daoyu Huang; Xiankun Yan; Frank Neumann 001 (Theor. Comput. Sci., 2025)