- Adaptivity in multi-level traffic simulation using experimental frames(2022)
Authors: Stig Bosmans, Toon Bogaerts, Wim Casteels, Siegfried Mercelis, Joachim Denil, Peter Hellinckx
- Learning to communicate with reinforcement learning for an adaptive traffic control system(2022)
Authors: Simon Vanneste, Gauthier de Borrekens, Stig Bosmans, Astrid Vanneste, Kevin Mets, Siegfried Mercelis, Steven Latré, Peter Hellinckx
Pages: 207 - 216
- Improving scalability of large scale agent-based simulations(2021)
Authors: Stig Bosmans, Peter Hellinckx, Joachim Denil
Number of pages: 126
- Adaptivity in Distributed Agent-Based Simulation(2021)
Authors: Stig Bosmans, Toon Bogaerts, Wim Casteels, Siegfried Mercelis, Joachim Denil, Peter Hellinckx
Pages: 1 - 12
- Designing resource-constrained neural networks using neural architecture search targeting embedded devices(2020)
Authors: Thomas Cassimon, Simon Vanneste, Stig Bosmans, Siegfried Mercelis, Peter Hellinckx
- Using neural architecture search to optimize neural networks for embedded devices(2020)
Authors: Thomas Cassimon, Simon Vanneste, Stig Bosmans, Siegfried Mercelis, Peter Hellinckx
Pages: 684 - 693
- Learning to communicate with multi-agent reinforcement learning using value-decomposition networks(2020)
Authors: Simon Vanneste, Astrid Vanneste, Stig Bosmans, Siegfried Mercelis, Peter Hellinckx
Pages: 736 - 745
- Cost-aware hybrid cloud scheduling of parameter sweep calculations using predictive algorithms(2019)
Authors: Stig Bosmans, Glenn Maricaux, Filip Van der Schueren, Peter Hellinckx
Pages: 63 - 75
- Enhancing students learning experience via low-cost network laboratories(2019)
Authors: Nina Slamnik-Krijestorac, Stig Bosmans, Peter Hellinckx, Johann Marquez-Barja
Pages: 34 - 40
- Reducing computational cost of large-scale simulations using opportunistic model approximation(2019)
Authors: Stig Bosmans, Siegfried Mercelis, Peter Hellinckx, Joachim Denil
Number of pages: 12
