Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...
The paper introduces a system model called the probabilistic asynchronous model which characterises the context in which many practical and the Internet-based applications are bui...
This paper presents a novel approach to achieve accurate and complete multi-view reconstruction of dynamic scenes (or 3D videos). 3D videos consist in sequences of 3D models in mot...
We address the problem of unsupervised image auto-annotation with probabilistic latent space models. Unlike most previous works, which build latent space representations assuming ...
We introduce a novel approach for robust belief tracking of user intention within a spoken dialog system. The space of user intentions is modeled by a probabilistic extension of t...
Neville Mehta, Rakesh Gupta, Antoine Raux, Deepak ...