Short-term Earthquake Prediction with Deep Neural Networks: Finding the optimal time prior to earthquake strikes to use in predictions

Earthquakes can have tremendous effects. They can result in casualties, massive damage, and hurt the economy. Therefore, one would like to predict earthquakes as early as possible and with the highest accuracy possible. This paper contains the proposal for the optimal prediction-time, which is the time between the execution of a prediction and...

COVID-19 Prediction and Mitigation

With the world in grasp of the COVID-19 pandemic, models predicting the spread of the virus can give indications to what extent a country is controlling the pandemic. Policymakers can decide to install so-called mitigation strategies to limit the spread of the virus. To aid the decision-making process, this report describes how a web application...

Modeling Inference Time of Deep Neural Networks on Memory-constrained Systems

Deep neural networks have revolutionized multiple fields within computer science. It is important to have a comprehensive understanding of the memory requirements and performance of deep networks on low-resource systems. While there have been efforts to this end, the effects of severe memory limits and heavy swapping are understudied. We have...

Predicting Football Outcomes: with Bayesian Networks

In this thesis Bayesian Networks are used to predict European football matches between the years 2008 and 2016. The goal of this research is to see how the structures learned by different Bayesian Network learning algorithms influences the predictions. First the data is explored and modified to be used for Bayesian Networks and secondly the...

The influence of learning algorithms for Bayesian Networks on predictions: A citation analysis study case

In this thesis, attention is paid to building different Bayesian networks. You can think of aspects such as parameter learning, search procedures and score functions. In addition, a distinction is made between the use of Discrete Bayesian Networks and Gaussian Networks. These models both have different assumptions which are also discussed. Finally...

Multimodal Interface for DNA Alignment of Sequences

Major research efforts in Bioinformatics include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution. To perform these specific tasks different tools are used. Using these tools separately is a...