The School of Informatics brings together research in Computer Science, Cognitive Science, Computational Linguistics and Artificial Intelligence. It provides a fertile environment for a wide range of interdisciplinary studies, leading to this new science of Informatics.

Recent Submissions

  • Program analysis of probabilistic programs 

    Gorinova, Maria I. (The University of Edinburgh, 2022-05-25)
    Probabilistic programming is a growing area that strives to make statistical analysis more accessible, by separating probabilistic modelling from probabilistic inference. In practice this decoupling is difficult. The ...
  • Controlling and Learning Constrained Motions for Manipulation in Contact 

    Pousa de Moura, João Miguel (The University of Edinburgh, 2021-10-31)
    Many practical tasks in robotic systems involving contact interaction with the environment, such as cleaning windows, writing or grasping, are inherently constrained, in that both the task and the environment impose ...
  • A Model Comparison between Neural Architectures of Human Bilingual Sentence Processing 

    Roslund, Rasmus (The University of Edinburgh, 2021-11-30)
    This work investigates phenomena related to human bilingual sentence processing in neural language models. We ask ourselves the question if and how the emergence of these phenomena depends on the model architecture. For ...
  • Modelling and spatio-temporal analysis of spatial stochastic systems 

    Luisa Vissat, Ludovica (The University of Edinburgh, 2019-07-01)
    [No Deposit Agreement]
  • Data-to-text generation with neural planning 

    Puduppully, Ratish Surendran (The University of Edinburgh, 2022-04-11)
    In this thesis, we consider the task of data-to-text generation, which takes non-linguistic structures as input and produces textual output. The inputs can take the form of database tables, spreadsheets, charts, and so ...
  • Foundations for programming and implementing effect handlers 

    Hillerström, Daniel (The University of Edinburgh, 2022-04-11)
    First-class control operators provide programmers with an expressive and efficient means for manipulating control through reification of the current control state as a first-class object, enabling programmers to implement ...
  • Identification and description of topics for newspaper comment summarisation 

    Llewellyn, Clare (The University of Edinburgh, 2018-11-29)
    [No Deposit Agreement]
  • Functional encryption: definitional foundations and multiparty transformations 

    Waldner, Hendrik (The University of Edinburgh, 2022-03-08)
    Classical cryptographic primitives do not allow for any fine-grained access control over encrypted data. From an encryption of some data x, a decryptor, who is in possession of a decryption key, can either obtain the ...
  • Traffic microstructures and network anomaly detection 

    Clausen, Henry (The University of Edinburgh, 2022-03-23)
    Much hope has been put in the modelling of network traffic with machine learning methods to detect previously unseen attacks. Many methods rely on features on a microscopic level such as packet sizes or interarrival times ...
  • 3D segmentation and localization using visual cues in uncontrolled environments 

    Cuevas Velasquez, Hanz (The University of Edinburgh, 2022-03-23)
    3D scene understanding is an important area in robotics, autonomous vehicles, and virtual reality. The goal of scene understanding is to recognize and localize all the objects around the agent. This is done through semantic ...
  • Creating data comics for data-driven storytelling 

    Wang, Zezhong (The University of Edinburgh, 2022-03-22)
    This doctoral thesis investigates research in understanding and creating data comics for datadriven storytelling. Data comic is a novel genre aiming to communicate insights from data through visualizations. Inspired by ...
  • Image classification over unknown and anomalous domains 

    Deecke, Lucas (The University of Edinburgh, 2022-03-21)
    A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to ...
  • Simulation methodologies for mobile GPUs 

    Kaszyk, Kuba (The University of Edinburgh, 2022-03-17)
    GPUs critically rely on a complex system software stack comprising kernel- and user-space drivers and JIT compilers. Yet, existing GPU simulators typically abstract away details of the software stack and GPU instruction ...
  • Digital asset management via distributed ledgers 

    Karakostas, Dimitris (The University of Edinburgh, 2022-03-16)
    Distributed ledgers rose to prominence with the advent of Bitcoin, the first provably secure protocol to solve consensus in an open-participation setting. Following, active research and engineering efforts have proposed a ...
  • Interactive task learning from corrective feedback 

    Appelgren, Mattias (The University of Edinburgh, 2022-03-16)
    In complex teaching scenarios it can be difficult for teachers to exhaustively express all information a learner requires to master a task. However, the teacher, who will have internalised the task's objectives, will be ...
  • An optimization-based formalism for shared autonomy in dynamic environments 

    Mower, Christopher (The University of Edinburgh, 2022-03-15)
    Teleoperation is an integral component of various industrial processes. For example, concrete spraying, assisted welding, plastering, inspection, and maintenance. Often these systems implement direct control that maps ...
  • Learning disentangled speech representations 

    Williams, Jennifer (The University of Edinburgh, 2022-03-15)
    A variety of informational factors are contained within the speech signal and a single short recording of speech reveals much more than the spoken words. The best method to extract and represent informational factors from ...
  • Effective attention-based sequence-to-sequence modelling for automatic speech recognition 

    Zhang, Shucong (The University of Edinburgh, 2022-03-14)
    With sufficient training data, attentional encoder-decoder models have given outstanding ASR results. In such models, the encoder encodes the input sequence into a sequence of hidden representations. The attention mechanism ...
  • Scalable software and models for large-scale extracellular recordings 

    Hurwitz, Cole Lincoln (The University of Edinburgh, 2022-03-11)
    The brain represents information about the world through the electrical activity of populations of neurons. By placing an electrode near a neuron that is firing (spiking), it is possible to detect the resulting extracellular ...
  • Machine learning applications for noisy intermediate-scale quantum computers 

    Coyle, Brian (The University of Edinburgh, 2022-03-09)
    Quantum machine learning (QML) has proven to be a fruitful area in which to search for applications of quantum computers. This is particularly true for those available in the near term, so called noisy intermediate-scale ...

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