We consider the problem of correcting the posterior marginal approximations computed by expectation propagation and Laplace approximation in latent Gaussian models and propose cor...
Improving on recent work on joint source-filter analysis of speech waveforms, we explore improvements to an autoregressive model with exogenous inputs represented by flexible ba...
We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size - two parameters known to bound the complexity...
Kalev Kask, Andrew Gelfand, Lars Otten, Rina Decht...
This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
We present an approach to high-level shape editing that adapts the structure of the shape while maintaining its global characteristics. Our main contribution is a new algebraic mo...
Martin Bokeloh, Michael Wand, Hans-Peter Seidel, V...