Scientific computing has experienced a surge empowered by advancements i...
Bayesian optimal experimental design is a sub-field of statistics focuse...
In temporal-difference reinforcement learning algorithms, variance in va...
Temporal-Difference (TD) learning methods, such as Q-Learning, have prov...
The recent increase in volume and complexity of available astronomical d...
In this work, we propose an infinite restricted Boltzmann machine (RBM),...
We study the problem of multi-person pose estimation in natural images. ...
Restricted Boltzmann machines (RBMs) and conditional RBMs (CRBMs) are po...
Marginal MAP inference involves making MAP predictions in systems define...
Distributed learning of probabilistic models from multiple data reposito...
Estimating statistical models within sensor networks requires distribute...