12 citations · 12 across the 16 of their papers we have counts for
8 papers · 1 filter
Extending FAIR Principles with Observability for Trustworthy Federated Learning
Hangli Ge, Noboru Koshizuka
Federated learning (FL) keeps data at its source, but locality alone does not make a federation trustworthy. Without sufficient observability, an aggregator cannot determine whethe…
Towards Efficient and Evidence-grounded Mobility Prediction with LLM-Driven Agent
Linyao Chen, Qinlao Zhao, Zechen Li +7
Individual-level mobility prediction is central to urban simulation, transportation planning, and policy analysis. Supervised sequence models achieve strong accuracy but require ta…
TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models
Peiran Li, Jiawei Wang, Haoran Zhang +4
The importance of mobile phone GPS trajectory data is widely recognized across many fields, yet the use of real data is often hindered by privacy concerns, limited accessibility, a…
TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer
Jiawei Wang, Chuang Yang, Jiawei Yong +6
Mobility trajectories are essential for understanding urban dynamics and enhancing urban planning, yet access to such data is frequently hindered by privacy concerns. This research…
Place with Intention: An Empirical Attendance Predictive Study of Expo 2025 Osaka, Kansai, Japan
Xiaojie Yang, Dizhi Huang, Hangli Ge +4
Accurate forecasting of daily attendance is vital for managing transportation, crowd flows, and services at large-scale international events such as Expo 2025 Osaka, Kansai, Japan.…
Deep Unfolding for MIMO Signal Detection
Hangli Ge, Noboru Koshizuka
In this paper, we propose a deep unfolding neural network-based MIMO detector that incorporates complex-valued computations using Wirtinger calculus. The method, referred as Dynami…
Causality-Aware Next Location Prediction Framework based on Human Mobility Stratification
Xiaojie Yang, Zipei Fan, Hangli Ge +3
Human mobility data are fused with multiple travel patterns and hidden spatiotemporal patterns are extracted by integrating user, location, and time information to improve next loc…
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events
Xiaojie Yang, Hangli Ge, Jiawei Wang +4
Large-scale human mobility exhibits spatial and temporal patterns that can assist policymakers in decision making. Although traditional prediction models attempt to capture these p…