BERT4Traj: Transformer Based Trajectory Reconstruction for Sparse Mobility Data

2025-07-03 · Hao Yang, Angela Yao, Christopher Whalen, Gengchen Mai arxiv

Understanding human mobility is essential for applications in public health, transportation, and urban planning. However, mobility data often suffers from sparsity due to limitations in data collection methods, such as infrequent GPS sampling or call detail record (CDR) data that only capture locations during communication events. To address this challenge, we propose BERT4Traj, a transformer based model that reconstructs complete mobility trajectories by predicting hidden visits in sparse movement sequences. Inspired by BERT's masked language modeling objective and self_attention mechanisms, BERT4Traj leverages spatial embeddings, temporal embeddings, and contextual background features such as demographics and anchor points. We evaluate BERT4Traj on real world CDR and GPS datasets collected in Kampala, Uganda, demonstrating that our approach significantly outperforms traditional models such as Markov Chains, KNN, RNNs, and LSTMs. Our results show that BERT4Traj effectively reconstructs detailed and continuous mobility trajectories, enhancing insights into human movement patterns.

📄 PDF Abstract BibTeX arXiv:2507.03062

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Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learning

2022-03-14 · Qinjie Lin, Han Liu, Biswa Sengupta

We propose SwitchTT, a multi-task extension to Trajectory Transformer but enhanced with two striking features: (i) exploiting a sparsely activated model to reduce computation cost in multi-task offline model learning and…

reinforcement-learning Reinforcement Learning (RL)

Transformer Networks for Trajectory Forecasting

2020-03-18 · Francesco Giuliari, Irtiza Hasan, Marco Cristani, Fabio Galasso

Most recent successes on forecasting the people motion are based on LSTM models and all most recent progress has been achieved by modelling the social interaction among people and the people interaction with the scene. W…

Trajectory Forecasting Trajectory Prediction

Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection

2026-03-26 · Md Awsafur Rahman, Chandrakanth Gudavalli, Hardik Prajapati, B. S. Manjunath arxiv

Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidence such as abnormal speeds and short-duration events, but their quadratic…

Semantic Segmentation Image Classification Anomaly Detection Fraud Detection

TIDE : Temporal-Aware Sparse Autoencoders for Interpretable Diffusion Transformers in Image Generation

2025-03-10 · Victor Shea-Jay Huang, Le Zhuo, Yi Xin, Zhaokai Wang 외

Diffusion Transformers (DiTs) are a powerful yet underexplored class of generative models compared to U-Net-based diffusion models. To bridge this gap, we introduce TIDE (Temporal-aware Sparse Autoencoders for Interpreta…

Denoising Image Generation Style Transfer

Modeling a Hidden Dynamical System Using Energy Minimization and Kernel Density Estimates

2019-04-08 · Trevor K. Karn, Steven Petrone, Christopher Griffin

In this paper we develop a kernel density estimation (KDE) approach to modeling and forecasting recurrent trajectories on a compact manifold. For the purposes of this paper, a trajectory is a sequence of coordinates in a…

Density Estimation Trajectory Modeling