Lin Wu

Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam

2018 · arXiv (Cornell University)

Uncertainty computation in deep learning is essential to design robust and reliable systems. Variational inference (VI) is a promising approach for such computation, but requires more effort to implement and execute compared to maximum-likelihood methods. …

MDPL-net: Multi-layer Dictionary Learning Network with Added Skip Dense Connections

2020

Dictionary learning (DL) is powerful for representation learning, while it fails to capture the deep hierarchical information hidden in data. In this paper, we propose a new generalized end-to-end mulita-layer representation learning architecture referred to …