We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
Generalized algebraic data types (GADTs), sometimes known as "guarded recursive data types" or "first-class phantom types", are a simple but powerful generaliz...
Simon L. Peyton Jones, Dimitrios Vytiniotis, Steph...
We present a novel method for detecting and quantifying 3D structure in stacks of microscopic images captured at incremental focal lengths. We express the image data as stochastic...