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Networks are commonly used to represent key processes in biology; examples include transcriptional regulatory networks, protein-protein interaction (PPI) networks, metabolic networks, etc. Databases store many such networks, as graphs, observed or inferred ...
Graphs are a prevalent tool in data science, as they model the inherent structure of the data. They have been used successfully in unsupervised and semi-supervised learning. Typically they are constructed either by connecting nearest samples, or by learnin ...
Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiri ...
Co-location information about users is increasingly available online. For instance, mobile users more and more frequently report their co-locations with other users in the messages and in the pictures they post on social networking websites by tagging the ...
State-of-the-art automatic speech recognition (ASR) and text-to-speech systems require a pronunciation lexicon that maps each word to a sequence of phones. Manual development of lexicons is costly as it needs linguistic knowledge and human expertise. To fa ...
Generalized linear models, where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform z = A x, arise in a range of applications in nonlinear filtering and regression. Approximate message passing (AMP) methods, b ...
We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...
For estimating parameters of discrete choice models, observations corresponding to the models are required. In the context of route choice models, we need the information of paths, which are sequences of links and connect between the origin-destination pa ...
Existing camera networks in public spaces such as train terminals or malls can help social robots to navigate crowded scenes. However, the localization of the cameras is required, i.e., the positions and poses of all cameras in a unique reference. In this ...
This master project's objectives are: - Understanding of the main approaches commonly used for discharge forecasting. - Understanding of key concepts of machine learning and evolutionary optimization. - Learning how to interpret discharge forecasts, both d ...