Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example. - Jason Z. Kim; Zhixin Lu; Erfan Nozari; George J. Pappas; Danielle S. Bassett (CoRR, 2020)

Resource Modeling of Power Communication Packet Optical Transport Network. - Zhixin Lu; Lianyu Fu; Yizhao Liu; Xiyang Yin (SmartCom, 2021)

Learning Continuous Chaotic Attractors with a Reservoir Computer. - Lindsay M. Smith; Jason Z. Kim; Zhixin Lu; Danielle S. Bassett (CoRR, 2021)

Teaching recurrent neural networks to infer global temporal structure from local examples. - Jason Z. Kim; Zhixin Lu; Erfan Nozari; George J. Pappas; Danielle S. Bassett (Nat. Mach. Intell., 2021)

A Novel Pseudo Nearest Neighbor Classification Method Using Local Harmonic Mean Distance. - Junzhuo Chen; Zhixin Lu; Shitong Kang (CoRR, 2024)

Hierarchy of chaotic dynamics in random modular networks. - Lukasz Kusmierz; Ulises Pereira-Obilinovic; Zhixin Lu; Dana Mastrovito; Stefan Mihalas (CoRR, 2024)

Social-Aware Learning-Based Online Energy Scheduling for 5G Integrated Smart Distribution Power Grid. - Lurui Jia; Haijun Liao; Zhenyu Zhou 001; Xiyang Yin; Zhongyu Wang; Yizhao Liu; Zhixin Lu; Guoyuan Lv; Wenbing Lu; Xiufan Ma; Xiaoyan Wang 003 (IEEE Trans. Comput. Soc. Syst., 2024)

Energy-Efficient Multi-Hop Routing Protocol for Tag-to-Tag Communication in Passive RFID Networks Using Reinforcement Learning. - Guowei Guo; Zeli Xi; Zhixin Lu; Ximei Zhan; Xinsen Yang; Peisong Li (IEEE Access, 2025)

High-order stochastic integration schemes for the Rosenbluth-Trubnikov collision operator in particle simulations. - Zhixin Lu; Guo Meng; Tomasz M. Tyranowski; Alex Chankin (J. Comput. Phys., 2025)

A Fokker-Planck-Based Loss Function that Bridges Dynamics with Density Estimation. - Zhixin Lu; Lukasz Kusmierz; Stefan Mihalas (CoRR, 2025)