Lise, Stefano, Archambeau, Cedric, Pontil, Massimiliano, Jones, David T
Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are...
Sparse probabilistic projections (2009)
Archambeau, Cedric, Bach, Francis
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as special cases. Sparsity...
The Variational Gaussian Approximation Revisited (2009)
Opper, Manfred, Archambeau, Cedric
The variational approximation of posterior distributions by multivariate Gaussians has been much less popular in the Machine Learning community compared to the corresponding approximation by...
Shen, Yuan, Archambeau, Cedric, Cornford, Dan, Opper, Manfred, Shawe-Taylor, John, Barillec, Remi
In recent years we have developed a novel variational method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational...
The Variational Gaussian Approximation Revisited. (2009)
Opper, Manfred, Archambeau, Cedric
The variational approximation of posterior distributions by multivariate Gaussians has been much less popular in the Machine Learning community compared to the corresponding approximation by...
Switching regulatory models of cellular stress response (2009)
Sanguinetti, Guido, Ruttor, Andreas, Opper, Manfred, Archambeau, Cedric
Motivation: Stress response in cells is often mediated by quick activation of transcription factors (TFs). Given the difficulty in experimentally assaying TF activities, several statistical...
Switching Regulatory Models of Cellular Stress Response (2008)
Sanguinetti, Guido, Ruttor, Andreas, Opper, Manfred, Archambeau, Cedric
Stress response in cells is often mediated by quick activation of transcription factors. Given the difficulty in experimentally assaying transcription factor activities, several statistical...
Sparse Probabilistic Projections (2008)
Archambeau, Cedric, Bach, Francis
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as special cases. Sparsity...
Standaert, Francois-Xavier, Archambeau, Cedric
The power consumption and electromagnetic radiation are among the most extensively used side-channels for analyzing physically observable cryptographic devices. This paper tackles three important...
Shen, Yuan, Archambeau, Cedric, Cornford, Dan, Opper, Manfred
In this paper, we develop a set of novel Markov chain Monte Carlo algorithms for Bayesian inference in partially observed non-linear diffusion processes. The Markov chain Monte Carlo algorithms we...
Shen, Yuan, Archambeau, Cedric, Cornford, Dan, Opper, Manfred, Shawe-Taylor, John, Barillec, Remi
In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the...
Flexible and Robust Bayesian Classification by Finite Mixture Models (2004)
Cedric Archambeau, Federic Vrins, Michel Verleysen
The regularized Mahalanobis distance is proposed in the framework of finite mixture models to avoid commonly faced numerical difficulties encountered with EM. Its principle is applied to Gaussian and...
Classification of Visual Sensations Generated Electrically in the Visual Field of the Blind (2003)
Cedric Archambeau, Jean Delbeke, Michel Verleysen
Within the framework of the OPTIVIP project, an optic nerve based visual prosthesis is being developed in order to restore partial vision to the blind. In this paper, we concentrate on the...