Bayesian Deep Learning
- Deep Additive Kernel Learning equips the last-layer GP in deep kernel learning with an additive structure and induced prior approximations, yielding an equivalent last-layer Bayesian neural network architecture that preserves interpretability while lowering the computational complexity.
Haoyuan Chen
Research Fellow
My research interests include Gaussian processes, uncerntainty quantification and probabilistic machine learning.