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Now showing items 26987-27006 of 41808
Machine learning for quantum physics and quantum physics for machine learning
Research at the intersection of machine learning (ML) and quantum physics is a recent growing field due to the enormous expectations and the success of both fields. ML is arguably one of the most promising technologies ...
Machine learning in multiscale modeling and simulations of molecular systems
Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. ...
Machine learning in structural biology and chemoinformatics : Driving drug discovery one epoch at a time
Deep learning approaches have become increasingly popular in the last years thanks to their state-of the-art performance in fields such as computer vision and natural language understanding. The first goal of this thesis ...
Machine learning methods for predicting days to discharge in Intensive Care Units patients
Les UCI donen atenció especialitzada per a pacients crítics, amb monitorització constant i equips d'atenció mèdica dedicats fins a la seva estabilitat per ser traslladats o donats d'alta. Una planificació inadequada pot ...
Machine learning methods for the analysis of liquid chromatography-mass spectrometry datasets in metabolomics
Liquid Chromatography-Mass Spectrometry (LC/MS) instruments are widely used in Metabolomics. To analyse their output, it is necessary to use computational tools and algorithms to extract meaningful biological information. ...
Machine learning methods for the characterization and classification of complex data
This thesis work presents novel methods for the analysis and classification of medical images and, more generally, complex data. First, an unsupervised machine learning method is proposed to order anterior chamber OCT ...
Machine learning methods for understanding social media communication: modeling irony and emojis
In this dissertation we propose algorithms for the analysis of social media texts, focusing on two particular aspects: irony and emojis. We propose novel automatic systems, based on machine learning methods, able to recognize ...
Machine learning techniques for adaptive polynomial and neural network digital predistorters
(English) The power amplifier (PA) is a core element in the radio transmitters to support the required mobile and fixed broadband communication link ranges. However, the PA is a power-hungry and nonlinear by nature device. ...
Machine Learning techniques in bioinformatics: From data integration to the development of application-oriented tools
Els darrers desenvolupaments en Machine Learning tenen com a objectiu automatitzar els mètodes disponibles, convertint-los en universals alhora que requerint el mínim coneixement expert possible. En aquesta tesi, farem un ...
Machine learning to support exploring and exploiting real-world clinical longitudinal data
Following-up on patient evolution by reacquiring the same measurements over time (longitudinal data) is a crucial component in clinical care dynamics, as it creates opportunity for timely decision making in preventing ...
Machine learning-based techniques for indoor localization and human activity recognition through wearable devices
This thesis approaches the study of several machine learning techniques to improve the performance of indoor positioning systems, with a special focus on wearable and low-cost devices. It also presents some tools designed ...
Machine translation in a professional translation workflow: post-editing or computer aided translation
Localization is a fascinating field which has changed dramatically in the last years and it is still changing and adapting itself as society is. The use of machine translation has developed this field astonishingly. Many ...
Machine Translationness: a Concept for Machine Translation Evaluation and Detection
La tradautomaticitat és el fenomen lingüístic que fa que les traduccions automàtiques sonin a màquina. Aquesta tesi introdueix el concepte de tradautomaticitat com un objecte de recerca i presenta un mètode d'avaluació que ...
Machine-Learning Applied Methods
The presented discourse followed several topics where every new chapter introduced an economic prediction problem and showed how traditional approaches can be complemented with new techniques like machine learning and deep ...
Machine-learning to promote better practices of low-cost wearable devices in tremor diseases
(English) The most common tremor disorders worldwide are Parkinson's Disease and Essential Tremor. The gold standard for diagnosing these movement disorders is medical evaluation by neurologists, but its accuracy depends ...
Machismo puertas adentro. Representaciones sociales sobre trabajo doméstico y trabajo de cuidados en parejas de doble ingreso de la ciudad de Talca, Chile.
En un escenario de intensas transformaciones sociales y familiares, y de búsqueda de equilibrio en la distribución de roles al interior de las familias, la conciliación del trabajo productivo y reproductivo emerge como un ...
Macro- and micro -symbioses involving sponges: Ecological roles in the marine benthos
The symbiotic lifestyle represents a fundamental contribution to the diversity of marine ecosystems. Sponges are ideal models to study symbiotic relationships from evolutionary and ecological points of view since they are ...
Macro- and microscopic analysis of the internet economy from network measurements
The growth of the Internet impacts multiple areas of the world economy, and it has become a permanent part of the economic landscape both at the macro- and at microeconomic level. On-line traffic and information are currently ...
Macro- and nanoscale self-assembled amino acid derivatives as reduction-sensitive and photoactive materials
Amino acid-based systems are attractive for biomedical applications given their high biocompatibility and functionality. Amino acids self-assemble into various structures ranging from a few nanometers to hundreds of microns ...
Macro-prudential policy via network analysis
The global financial crisis of 2007-2009 has demonstrated that the financial system should be regarded as a complex network whose nodes are financial institutions and links are financial dependencies. Since the financial ...
