Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
Image filtering is often applied as a post-process to Monte Carlo generated pictures, in order to reduce noise. In this paper we present an algorithm based on density estimation t...
We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatiotemporal spectral representation of the acoust...
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
Recent advances in statistical machine translation have used approximate beam search for NP-complete inference within probabilistic translation models. We present an alternative ap...
Abhishek Arun, Barry Haddow, Philipp Koehn, Adam L...