Feed-forward Neural Networks with Trainable Delay. - Xunbi A. Ji; Tamás G. Molnár; Sergei S. Avedisov; Gábor Orosz (L4DC, 2020)

Bayesian Inference for Time Delay Systems with Application to Connected Automated Vehicles. - Xunbi A. Ji; Tamás G. Molnár; Alex A. Gorodetsky; Gábor Orosz (ITSC, 2021)

Learning the Dynamics of Time Delay Systems with Trainable Delays. - Xunbi A. Ji; Tamás G. Molnár; Sergei S. Avedisov; Gábor Orosz (L4DC, 2021)

On-Board Traffic Prediction for Connected Vehicles: Implementation and Experiments on Highways. - Tamás G. Molnár; Xunbi A. Ji; Sanghoon Oh; Dénes Takács; Michael Hopka; Devesh Upadhyay; Michiel Van Nieuwstadt; Gábor Orosz (ACC, 2022)

Learning Time Delay Systems with Neural Ordinary Differential Equations. - Xunbi A. Ji; Gábor Orosz (CoRR, 2022)

Learning the dynamics of autonomous nonlinear delay systems. - Xunbi A. Ji; Gábor Orosz (L4DC, 2023)

Fundamental Rules of Teleoperated Driving with Network Latency on Curvy Roads. - Xunbi A. Ji; Sergei S. Avedisov; Mohammad Irfan Khan; M. Carmen Lucas-Estañ; Baldomero Coll-Perales; Illés Vörös; Onur Altintas; Gábor Orosz (IV, 2024)

Trainable Delays in Time Delay Neural Networks for Learning Delayed Dynamics. - Xunbi A. Ji; Gábor Orosz (IEEE Trans. Neural Networks Learn. Syst., 2025)