Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data

arXiv:2610.13557 · cs.LG, cs.RO · Submitted 2026-10-09 · Read on arXiv

cs.LG, cs.RO

Submitted: 2026-10-09

Updated: 2026-10-09

Comments: Manuscript written in 2021. 16 pages, 5 figures, 5 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• AIS Data — 1× in this paper · explained in 1 episode
• Transformer — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
• BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
• Language Models are Few-Shot Learners
• Linformer: Self-Attention with Linear Complexity
• Reformer: The Efficient Transformer
• Rethinking Attention with Performers
• Conditional Generative Adversarial Nets
• Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks