Concept

Bayesian network

Related publications (338)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models

Silvia Chiappa

Linear Gaussian State-Space Models are widely used and a Bayesian treatment of parameters is therefore of considerable interest. The approximate Variational Bayesian method applied to these models is an attractive approach, used successfully in application ...

2006

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models

Silvia Chiappa

IDIAP2006

A Bayesian Alternative to Gain Adaptation in Autoregressive Hidden Markov Models

Bertrand Mesot

Models dealing directly with the raw acoustic speech signal are an alternative to conventional feature-based HMMs. A popular way to model the raw speech signal is by means of an autoregressive (AR) process. Being too simple to cope with the nonlinearity of ...

IDIAP2006

Posterior Based Keyword Spotting with A Priori Thresholds

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

In this paper, we propose a new posterior based scoring approach for keyword and non keyword (garbage) elements. The estimation of these scores is based on HMM state posterior probability definition, taking into account long contextual information and the ...

2006

Posterior Based Keyword Spotting with A Priori Thresholds

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

IDIAP2006

Exploiting Binary Abstractions in Deciphering Gene Interactions

Giovanni De Micheli, Abhishek Garg

We consider computationally reconstructing gene regulatory networks on top of the binary abstraction of gene expression state information. Unlike previous Boolean network approaches, the proposed method does not handle noisy gene expression values directly ...

2006

Spin Glass Models of Markov Random Fields

Barbara Caputo

This paper presents a novel algorithm for robust object recognition. We propose to model the visual appearance of objects via probability density functions. The algorithm consists of a fully connected Markov random field with energy function derived from r ...

2006

Rating of Routing by Redundancy Overall Need

Emin Gabrielyan

Thanks to the large buffering time of off-line streaming applications, erasure resilient Forward Error Correction (FEC) codes can improve the reliability of communication particularly well. However real-time streaming puts hard restrictions on the buffer s ...

2006

Learning influence among interacting Markov chains

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

We present a model that learns the influence of interacting Markov chains within a team. The proposed model is a dynamic Bayesian network (DBN) with a two-level structure: individual-level and group-level. Individual level models actions of each player, an ...

IDIAP2005

Learning influence among interacting Markov chains

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

2005