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.

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Recent Submissions

  • Semantics and provenance of configuration programming language μPuppet 

    Fu, Weili (The University of Edinburgh, 2019-11-23)
    Nowadays computing infrastructures have grown bigger in scale and more complex. Automated configuration management tools have taken the place of traditional approaches of configuration tasks, such as manual configuration ...
  • Machine learning for inductive theorem proving 

    Jiang, Yaqing (The University of Edinburgh, 2019-11-23)
    Over the past few years, machine learning has been successfully combined with automated theorem provers (ATPs) to prove conjectures from various proof assistants. However, such approaches do not usually focus on inductive ...
  • Usability evaluation of spoken humanoid embodied conversational agents in mobile serious games 

    Korre, Danai (The University of Edinburgh, 2019-11-23)
    The use of embodied conversational agents (ECAs) and spoken dialogue systems in serious games offers theoretical advantages such as a more natural interaction with an agent displaying characteristics like personality, ...
  • Wide-coverage statistical parsing with minimalist grammars 

    Torr, John Philip (The University of Edinburgh, 2019-11-23)
    Syntactic parsing is the process of automatically assigning a structure to a string of words, and is arguably a necessary prerequisite for obtaining a detailed and precise representation of sentence meaning. For many NLP ...
  • Moving beyond parallel data for neutral machine translation 

    Currey, Anna (The University of Edinburgh, 2019-11-23)
    The goal of neural machine translation (NMT) is to build an end-to-end system that automatically translates sentences from the source language to the target language. Neural machine translation has become the dominant ...
  • Machine learning and privacy preserving algorithms for spatial and temporal sensing 

    Ghosh, Abhirup (The University of Edinburgh, 2019-11-23)
    Sensing physical and social environments are ubiquitous in modern mobile phones, IoT devices, and infrastructure-based settings. Information engraved in such data, especially the time and location attributes have ...
  • Methodology to sustain common information spaces for research collaborations 

    Trani, Luca (The University of Edinburgh, 2019-11-23)
    Information and knowledge sharing collaborations are essential for scientific research and innovation. They provide opportunities to pool expertise and resources. They are required to draw on today’s wealth of data to ...
  • Learning to make decisions with unforeseen possibilities 

    Innes, Craig (The University of Edinburgh, 2019-11-23)
    Methods for learning optimal policies often assume that the way the domain is conceptualised— the possible states and relevant actions that are needed to solve one’s decision problem—is known in advance and does not ...
  • Deep generative modelling for amortised variational inference 

    Srivastava, Akash (The University of Edinburgh, 2019-11-23)
    Probabilistic and statistical modelling are the fundamental frameworks that underlie a large proportion of the modern machine learning (ML) techniques. These frameworks allow for the practitioners to develop tailor-made ...
  • Phenomenological modelling: statistical abstraction methods for Markov chains 

    Michaelides, Michalis (The University of Edinburgh, 2019-11-23)
    Continuous-time Markov chains have long served as exemplary low-level models for an array of systems, be they natural processes like chemical reactions and population fluctuations in ecosystems, or artificial processes ...
  • From software to hardware: making dynamic multi-core processors practical 

    Micolet, Paul-Jules René Régis (The University of Edinburgh, 2019-11-23)
    Heterogeneous processors such as Arm’s big.LITTLE have become popular as they offer a choice between performance and energy efficiency. However, the core configurations are fixed at design time which offers a limited ...
  • Computational methods for the analysis of non-cell-autonomous phenomena and derived gene co-expression networks 

    Heron, Samuel (The University of Edinburgh, 2019-11-23)
    Non-cell-autonomous effects are the changes observed in one cell or cell-type as a consequence of the actions of another. The study of these phenomena is crucial to our understanding of how diverse cell-types function ...
  • Exploring the optimization space of multi-core architectures with OpenCL benchmarks 

    Panickal, Deepak (The University of Edinburgh, 2011)
    Open Computing Language (OpenCL) is an open standard for writing portable software for heterogeneous architectures such as Central Processing Units (CPUs) and Graphic Processing Units (GPUs). Programs written in OpenCL ...
  • Learning about the learning process: from active querying to fine-tuning 

    Pang, Kunkun (The University of Edinburgh, 2019-07-01)
    The majority of research on academic machine learning addresses the core model fitting part of the machine learning workflow. However, prior to model fitting, data collection and annotation is an important step; and ...
  • Weakly supervised sentiment analysis and opinion extraction 

    Angelidis, Stefanos (The University of Edinburgh, 2019-07-01)
    In recent years, online reviews have become the foremost medium for users to express their satisfaction, or lack thereof, about products and services. The proliferation of user-generated reviews, combined with the rapid ...
  • In search of the optimal acoustic features for statistical parametric speech synthesis 

    Espic Calderón, Felipe Sebastián (The University of Edinburgh, 2019-07-01)
    In the Statistical Parametric Speech Synthesis (SPSS) paradigm, speech is generally represented as acoustic features and the waveform is generated by a vocoder. A comprehensive summary of state-of-the-art vocoding ...
  • Contextual citation recommendation using scientific discourse annotation schemes 

    Duma, Daniel Cristian (The University of Edinburgh, 2019-07-01)
    All researchers have experienced the problem of fishing out the most relevant scientific papers from an ocean of publications, and some may have wished that their text editor suggested these papers automatically. This ...
  • Language-integrated provenance 

    Fehrenbach, Stefan (The University of Edinburgh, 2019-07-01)
    Provenance is metadata about the where, the why, and the how of data. It is evidence which can answer questions such as: Where exactly did this piece of data come from? Why is this row in my result? How was it produced? ...
  • Statistical modelling of neuronal population activity: from data analysis to network function 

    Sorbaro Sindaci, Martino (The University of Edinburgh, 2019-07-01)
    The term statistical modelling refers to a number of abstract models designed to reproduce and understand the statistical properties of the activity of neuronal networks at the population level. Large-scale recordings ...
  • Stochastic modelling of spatial collective adaptive systems 

    Zoń, Natalia (The University of Edinburgh, 2019-07-01)
    Collective Adaptive Systems (CAS) are composed of individual agents with internal knowledge and rules which organize themselves into ensembles. These ensembles can often be observed to exhibit behaviour resembling that ...

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