4 papers · 1 filter
A Pretrained Probabilistic Transformer for City-Scale Traffic Volume Prediction
Shiyu Shen, Bin Pan, Guirong Xue
City-scale traffic volume prediction plays a pivotal role in intelligent transportation systems, yet remains a challenge due to the inherent incompleteness and bias in observationa…
Domain Generalization Guided by Large-Scale Pre-Trained Priors
Zongbin Wang, Bin Pan, Shiyu Shen +2
Domain generalization (DG) aims to train a model from limited source domains, allowing it to generalize to unknown target domains. Typically, DG models only employ large-scale pre-…
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions
Shiyu Shen, Bin Pan, Tianyang Shi +2
Domain invariant learning aims to learn models that extract invariant features over various training domains, resulting in better generalization to unseen target domains. Recently,…
Be Bayesian by Attachments to Catch More Uncertainty
Shiyu Shen, Bin Pan, Tianyang Shi +2
Bayesian Neural Networks (BNNs) have become one of the promising approaches for uncertainty estimation due to the solid theorical foundations. However, the performance of BNNs is a…