Informatics, School of

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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Insect neuroethology of reinforcement learning
(The University of Edinburgh, 2023-03-28)Historically, reinforcement learning is a branch of machine learning founded on observations of how animals learn. This involved collaboration between the fields of biology and artificial intelligence that was beneficial ... -
Planning automated guided vehicle movements in a factory
(The University of Edinburgh, 1988)This dissertation examines the problems of planning automated guided vehicle (AGV) movement schedules in an automated factory. AGVs are used mainly for material delivery and will have an important role in linking "islands ... -
Bayesian scalar-on-image regression via random image partition models: automatic identification of regions of interest
(The University of Edinburgh, 2023-03-21)Scalar-on-image regression aims to investigate changes in a scalar response of interest based on high-dimensional imaging data. These problems are increasingly prevalent in numerous domains, particularly in biomedical ... -
Using local linguistic context for text-to-speech
(The University of Edinburgh, 2023-03-15)Synthetic speech generated by state-of-the-art Text-to-Speech (TTS) models achieves unprecedented levels of naturalness. Training, inference and evaluation of TTS models has consistently been performed on isolated utterances ... -
Spiritual polarisation on social media: the case of Arab atheists on Twitter
(The University of Edinburgh, 2023-02-22)Social media platforms provide an unprecedented method of communication, and they are considered an integral part of people's lifestyles. Also, these platforms facilitate forming communities, groups and networks. Hence, ... -
Use of proxies in designing for and with autistic children: supporting friendship as a case study
(The University of Edinburgh, 2023-02-20)Participatory Design (PD) is an approach for designing new technologies which involves end users in the design process. It is generally accepted that involving users in the design process gives them a sense of ownership ... -
Zero-cost abstractions for irregular data shapes in a high-performance parallel language
(The University of Edinburgh, 2023-02-15)Modern parallel accelerators offer an unprecedented degree of performance, and are used pervasively in important application domains, such as High Performance Computing and Machine Learning. However, these accelerators ... -
Neural distribution estimation as a two-part problem
(The University of Edinburgh, 2023-02-14)Given a dataset of examples, distribution estimation is the task of approximating the assumed underlying probability distribution from which those samples were drawn. Neural distribution estimation relies on the powerful ... -
Generalising weighted model counting
(The University of Edinburgh, 2023-02-14)Given a formula in propositional or (finite-domain) first-order logic and some non-negative weights, weighted model counting (WMC) is a function problem that asks to compute the sum of the weights of the models of the ... -
Meta-learning to optimise: loss functions and update rules
(The University of Edinburgh, 2023-02-07)Meta-learning, aka “learning to learn”, aims to extract invariant meta-knowledge from a group of tasks in order to improve the generalisation of the base models in the novel tasks. The learned meta-knowledge takes various ... -
Task planning and the Connect-R: explainable AI for real world multi-robot system deployment
(The University of Edinburgh, 2023-02-06)The Connect-R is a novel Multi-Robot System that is intended to provide maintenance and servicing capabilities in nuclear environments. The Connect-R system is intended to address the problem of mitigating the effects of ... -
Program synthesis for heterogenous accelerators
(The University of Edinburgh, 2018-11-29)[No Deposit Agreement] -
Extensions to randomized benchmarking for digital and analogue near-term quantum devices
(The University of Edinburgh, 2023-02-01)The distant promise of a full-scale fault-tolerant universal quantum computer offers a speed-up in run-time for certain problems compared to the best classical algorithms. Inevitably, attention has fallen on the quantum ... -
Path integration system of insects: there and back again
(The University of Edinburgh, 2023-01-31)Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems ... -
Low- and high-resource opinion summarization
(The University of Edinburgh, 2023-01-25)Customer reviews play a vital role in the online purchasing decisions we make. The reviews express user opinions that are useful for setting realistic expectations and uncovering important details about products. However, ... -
Learning the structure of clusters in graphs
(The University of Edinburgh, 2023-01-25)Graph clustering is a fundamental problem in unsupervised learning, with numerous applications in computer science and in analysing real-world data. In many real-world applications, we find that the clusters have a significant ... -
Data-efficient neural network training with dataset condensation
(The University of Edinburgh, 2023-01-24)The state of the art in many data driven fields including computer vision and natural language processing typically relies on training larger models on bigger data. It is reported by OpenAI that the computational cost to ... -
FluiDB: adaptive storage layout using reversible relational operators
(The University of Edinburgh, 2023-01-20)It is a popular practice to use materialized intermediate results to improve the perfor- mance of RDBMSes. Work in this area has focused either optimisers matching existing materialized results in the cache and selecting ... -
Visual system identification: learning physical parameters and latent spaces from pixels
(The University of Edinburgh, 2023-01-20)In this thesis, we develop machine learning systems that are able to leverage the knowledge of equations of motion (scene-specific or scene-agnostic) to perform object discovery, physical parameter estimation, position ... -
Characterising the source of errors for metagenomic taxonomic classification
(The University of Edinburgh, 2023-01-19)Characterising microbial communities enables a better understanding of their complexity and the contribution to the environment. Metagenomics has been a rapidly expanding field since the revolution of next generation ...