LAIV Publications

2021 -22 Conference Publications:

  • D. Kienitz, E. Komendantskaya and M. Lones. The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI’22), Online.
  • AnalyZr: A Python application for zircon grain image segmentation and shape analysis Taryn Scharf, Chris Kirkland, Matthew Daggitt, Milo Barham, Vladimir Puzyrev. Computers & Geosciences 2022
  • Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick. Actions You Can Handle: Dependent Types for AI Plans. Workshop on Type-driven Development’ 21, at ICFP’21, 2021.
  • Marco CasadioMatthew L. Daggitt, Ekaterina Komendantskaya, Wen KokkeDaniel KienitzRob Stewart: Property-driven Training: All You (N)Ever Wanted to Know About. CoRR abs/2104.01396 (2021)
  • Kirsty Duncan, Robert Stewart and Ekaterina Komendantskaya.  Logically Constrained Pruning Towards Robust Neural Networks. FOMLAS’21, Workshop on Formal Methods for ML-Enabled Autonomous Systems, at CAV’21.

2021 BSc and MSc dissertations:

Natalia Slusarz: Mathematical Properties of Neural Networks Trained on Artificial Data Sets. BSc Dissertation at Heriot-Watt University, 2021. Supervisors: E.Komendantskaya and D.Kienitz

Remi Desmartin: Neural Network Verification with Imandra. MSc Dissertation at Heriot-Watt University, 2021. Best Dissertation award. Supervisors: E.Komendantskaya and M.Daggitt

Dan Green: Understanding the Role of Machine Learning in Signed Language Recognition. Supervisors: E.Komendantskaya and M.Daggitt

Michael Pidgeon: Building Trust in Explanations of Machine Learning tools. MSc Dissertation at Heriot-Watt University, 2021. Supervisors: E.Komendantskaya and M.Daggitt

2020 Conference Publications:

2020 MSc and PhD Dissertations:

  • Alexandre Cardaillac. Explainable AI: Methods to Evaluate Machine Learning Models. MSc Dissertation. 2020. Supervisor: E.Komendantskaya.
  • Marco Casadio. Generative Against Logical Training against Adversarial Attacks. MSc Dissertation. 2020. Supervisor: E.Komendantskaya.
  • Hugo Cousin. High-performance Data Analysis for Social Networks Using Rust. MSc Dissertation. 2020. Supervisor: H.-W. Loidl.
  • Fraser Garrow. Artificial Neural Network Genetic Improvement for Accurate and Robust Image Classification. MSc Dissertation. 2020. Supervisor: M.Lones.
  • Dorian Gouzou. Repelling Dual-Swarm Particle Optimisation with Maximisation search. MSc Dissertation. 2020. Supervisor: M.Lones.
  • Vincent Larcher. Generation of Adversarial Attacks on Computer Vision Models using Reinforcement Learning. MSc Dissertation. 2020. Supervisor: E.Komendantskaya.
  • Bartosz Schatton. Informed Adversarial Examples with Explainable AI and Metaheuristics in Medical Imaging. MSc Dissertation. 2020. Supervisor: E.Komendantskaya.
  • Frantisek Farka. Proof-Relevant Resolution: The Foundations of Constructive Proof Automation. PhD Dissertation. 2020. Supervisor: E.Komendantskaya.

2019 Conference papers:

2019 MSc and PhD Dissertations:

  • P. Bacchus. Performance Metrics for Approximate Deep Learning on Programmable Hardware. MSc Thesis, Heriot-Watt University, 2019. Supervisor: R. Stewart.
  • P. Le Hen. Adversarial Attacks on Neural Networks in Image Processing. MSc Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya.
  • D. Kienitz. Robustness of Neural Networks: Understanding the Nature of Adversarial Examples. MSc Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya.
  • Y.Li. A Proof-Theoretic Approach to Coinduction in Horn Clause Logic” . PhD Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya and M.Lawson.