LAIV Publications

2020:

Pascal Bacchus, Robert Stewart and Ekaterina Komendantskaya. Accuracy, Training Time and Hardware Efficiency Trade-Offs for Quantised Neural Networks on FPGAs. 16th International Symposium on Applied Reconfigurable Computing (ARC2020), 1-3 April   Toledo, Spain.

2019:

  1. C.Schwaab, E.Komendantskaya, A.Hill, F.Farka, J.Wells, R.Petrick, K.Hammond. Proof-Carrying Plans. PADL 2019 (21st International Symposium on Practical Aspects of Declarative Languages), 14-15 January 2019, Cascais/Lisbon, Portugal.
  2. H. Basold, E. Komendantskaya, Y. Li Coinduction in Uniform: Foundations for Corecursive Proof Search with Horn Clauses. ESOP 2019 (28th European Symposium on Programming), 8-11 April 2019, Prague.
  3. E. Komendantskaya, R. Stewart, K. Duncan, D. Kienitz, P. Le Hen, P. Bacchus. Neural Network Verification for the Masses (of AI graduates). Experience report, June 2019
  4. P. Bacchus. Performance Metrics for Approximate Deep Learning on Programmable Hardware. MSc Thesis, Heriot-Watt University, 2019. Supervisor: R. Stewart.
  5. P. Le Hen. Adversarial Attacks on Neural Networks in Image Processing. MSc Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya.
  6. D. Kienitz. Robustness of Neural Networks: Understanding the Nature of Adversarial Examples. MSc Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya.
  7. Y.Li. A Proof-Theoretic Approach to Coinduction in Horn Clause Logic” . PhD Thesis, Heriot-Watt University, 2019. Supervisor: E.Komendantskaya and M.Lawson.