Efficiently coupling QM and MD for the study of electrode-electrolyte interfaces

In this thesis, a proof of concept was established for the use of a novel coupled QM-MD approach to modelling metallic (copper) electrode-electrolyte interfaces. SCC-DFTB calculations of the instantaneous electronic structure of a copper electrode were coupled to a classical MD simulation of an electrode-electrolyte interface. The applied QM-MD...

A Generative Neural Network Model for Speech Enhancement

Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...

Evaluating and Improving Large-Scale Machine Learning Frameworks

Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...

Exploring Gravitational Waves Recordings with Machine Learning Techniques

The study of Gravitational Waves (GWs) opened a new window of possibilities to improve our understanding of the Universe. GWs provide suitable astronomical messengers for studying events that were not possible before through electromagnetic radiation, or in other cases complementing their observations. Ground-based interferometers like LIGO have...

Automatic keypoint detecting of wireframe gates

This work applies keypoint detection method to solve gate recognition problem. Unlike regular object detection task, gate recognition problem is made difficult by the fact that gate is empty wireframe which means that the object surrounded by gate-edge is not relevant and should not be taken into consideration when detecting. However, regular...

Deep vs Shallow Reinforcement Learning for low dimensional continuous control tasks

Deep Learning performance dependents on the application and methodology. Neural Networks with convolutional layers have been a great success in multiple tasks trained under Supervised Learning algorithms. For higher dimensional problems, the selection of a deep network architecture can significantly improve the accuracy of the network, however...

Solving Partial Differential Equations with Neural Networks

Recent works have shown that neural networks can be employed to solve partial differential equations, bringing rise to the framework of physics informed neural networks.The aim of this project is to gain a deeper understanding of these novel methods, and to use these insights to further improve them. We show that solving a partial differential...

Nerve fiber tracing in bright-field images of human skin using deep learning

The goal of this thesis is to find an automated method that can trace all nerve fibers in bright-field images of skin tissue. This is an important step towards the automated quantification of intra-epidermal nerve fiber density, an important biomarker in the diagnosis of small-fiber neuropathy.<br/>Deep learning is a popular new field of...

Visualization Methods for Understanding Deep Neural Networks

Generating Robotic Manipulation Trajectories with Neural Networks

In order to interact with environments and appliances made for humans, robots should be able to manipulate a large variety of objects and appliances in human environments. When having experience with manipulating a certain object or appliance, a robot should be able to generalize this behaviour to novel, but similar objects and appliances. When...

Een Semantisch Connectionistisch Redeneersysteem (SCORE)

Het onderzoek heeft zich gericht op de ontwikkeling van een Semantisch Connectionistisch Redeneersysteem (SCORE). SCORE kan de basis vormen voor een volwaardig expertsysteem. De, voor een expertsysteem van elementair belang zijnde, fundamentele inferentie principes, kennisacquisitie principes en kennisrepresentatievormen hebben in SCORE de...