Now showing items 21-40 of 1545

    • Resource management in future mobile networks: from millimetre-wave backhauls to airborne access networks 

      Li, Rui (The University of Edinburgh, 2019-07-01)
      The next generation of mobile networks will connect vast numbers of devices and support services with diverse requirements. Enabling technologies such as millimetre-wave (mm-wave) backhauling and network slicing allow ...
    • Models for reinforcement learning and design of a soft robot inspired by Drosophila larvae 

      Wei, Tianqi (The University of Edinburgh, 2019-07-01)
      Designs for robots are often inspired by animals, as they are designed mimicking animals’ mechanics, motions, behaviours and learning. The Drosophila, known as the fruit fly, is a well-studied model animal. In this thesis, ...
    • Data driven mapping of the drosophila larval central nervous system 

      Wood, David George (The University of Edinburgh, 2019-07-01)
      The Central Nervous System (CNS) of the larval Drosophila model organism is extensively studied partly due to its small size and short generation times but also due to its ability to learn and the availability of genetic ...
    • Fast machine translation on parallel and massively parallel hardware 

      Bogoychev, Nikolay Veselinov (The University of Edinburgh, 2019-07-01)
      Parallel systems have been widely adopted in the field of machine translation, because the raw computational power they offer is well suited to this computationally intensive task. However programming for parallel hardware ...
    • Verification problems for timed and probabilistic extensions of Petri Nets 

      Ciobanu, Radu (The University of Edinburgh, 2019-07-01)
      In the first part of the thesis, we prove the decidability (and PSPACE-completeness) of the universal safety property on a timed extension of Petri Nets, called Timed Petri Nets. Every token has a real-valued clock (a.k.a. ...
    • Learning structured task related abstractions 

      Penkov, Svetlin Valentinov (The University of Edinburgh, 2019-07-01)
      As robots and autonomous agents are to assist people with more tasks in various domains they need the ability to quickly gain contextual awareness in unseen environments and learn new tasks. Current state of the art ...
    • Typed concurrent functional programming with channels, actors and sessions 

      Fowler, Simon John (The University of Edinburgh, 2019-07-01)
      The age of writing single-threaded applications is over. To develop scalable applications, developers must make use of concurrency and parallelism. Nonetheless, introducing concurrency and parallelism is difficult: naïvely ...
    • Way of the dagger 

      Karvonen, Martti Johannes (The University of Edinburgh, 2019-07-01)
      A dagger category is a category equipped with a functorial way of reversing morphisms, i.e. a contravariant involutive identity-on-objects endofunctor. Dagger categories with additional structure have been studied under ...
    • On accuracy, robustness and reliability of laser-based localization 

      Nobili, Simona (The University of Edinburgh, 2019-07-01)
      Legged robots are expected to demonstrate autonomous skills in situations which are not suitable for wheeled platforms, such as cluttered disaster areas and outdoor trails. State estimation strategies for legged robots ...
    • Visual context for verb sense disambiguation and multilingual representation learning 

      Gella, Spandana (The University of Edinburgh, 2019-07-01)
      Every day billions of images are uploaded to the web. To process images at such a large scale it is important to build automatic image understanding systems. An important step towards understanding the content of the ...
    • Spatial statistical modelling of epigenomic variability 

      Kapourani, Chantriolnt Andreas (The University of Edinburgh, 2019-07-01)
      Each cell in our body carries the same genetic information encoded in the DNA, yet the human organism contains hundreds of cell types which differ substantially in physiology and functionality. This variability stems ...
    • Developing a framework for semi-automated rule-based modelling for neuroscience research 

      Wysocka, Emilia Malgorzata (The University of Edinburgh, 2019-07-01)
      Dynamic modelling has significantly improved our understanding of the complex molecular mechanisms underpinning neurobiological processes. The detailed mechanistic insights these models offer depend on the availability ...
    • Probabilistic graph formalisms for meaning representations 

      Gilroy, Sorcha (The University of Edinburgh, 2019-07-01)
      In recent years, many datasets have become available that represent natural language semantics as graphs. To use these datasets in natural language processing (NLP), we require probabilistic models of graphs. Finite-state ...
    • Advances in scene understanding: object detection, reconstruction, layouts, and inference 

      Henderson, Paul Matthew (The University of Edinburgh, 2019-07-01)
      The goal of scene understanding is to capture the full content of an image in a human-interpretable representation. This must describe the different objects present, including their attributes such as class, shape, and ...
    • Learning natural language interfaces with neural models 

      Dong, Li (The University of Edinburgh, 2019-07-01)
      Language is the primary and most natural means of communication for humans. The learning curve of interacting with various devices and services (e.g., digital assistants, and smart appliances) would be greatly reduced ...
    • Lifecycle of neural semantic parsing 

      Cheng, Jianpeng (The University of Edinburgh, 2019-07-01)
      Humans are born with the ability to learn to perceive, comprehend and communicate with language. Computing machines, on the other hand, only understand programming languages. To bridge the gap between humans and computers, ...
    • Vision as inverse graphics for detailed scene understanding 

      Moreno Comellas, Pol (The University of Edinburgh, 2019-07-01)
      An image of a scene can be described by the shape, pose and appearance of the objects within it, as well as the illumination, and the camera that captured it. A fundamental goal in computer vision is to recover such ...
    • Low-resource learning in complex games 

      Dobre, Mihai Sorin (The University of Edinburgh, 2019-07-01)
      This project is concerned with learning to take decisions in complex domains, in games in particular. Previous work assumes that massive data resources are available for training, but aside from a few very popular games, ...
    • Permission impossible - the design and evaluation of a video game that teaches beginners about firewalls 

      Sehl, Sibylle Katharina (The University of Edinburgh, 2017-11-30)
      Firewalls are a complex piece of software that present challenges to novices and experienced users alike. Recent years have seen an increased need for computer security knowledge and awareness to prevent a growing number ...
    • Dimensionality reduction for EMG prediction of upper-limb activity in freely-behaving primates 

      Krasoulis, Agamemnon (The University of Edinburgh, 2013-11-28)
      Neural prosthetic systems aim to assist patients suffering from sensory, motor and other disabilities by translating neural brain activity into control signals for assistive devices, such as computers and robotics ...