| Machine learning in architecture: An overview of existing tools I Vukorep, A Kotov The Routledge Companion to Artificial Intelligence in Architecture, 93-109, 2021 | 9 | 2021 |
| Gridworld architecture testbed A Kotov, I Vukorep Towards a new, configurable architecture-Proceedings of the 39th eCAADe …, 2021 | 2 | 2021 |
| Quasi-Decentralized Cyber-Physical Fabrication Systems—A Practical Overview I Vukorep, A Kotov Architecture and Design for Industry 4.0: Theory and Practice, 185-200, 2023 | | 2023 |
| Spatial Agent-based Architecture Design Simulation Systems A Kotov, R Starke, I Vukorep Legal Depot D/2022/14982/02, 105, 2022 | | 2022 |
| AIAAF 2021-Symposium Report I Vukorep, A Kotov, CH Huang, G Rossi, V Sardenberg, L Atanasova, ... Inik eV, 2022 | | 2022 |
| While there is a broad spectrum of architectural design and analysis methods, machine learn-ing (ML) tools are filling a narrow niche commonly used by architects with … I Vukorep, A Kotov The Routledge Companion to Artificial Intelligence in Architecture, 93, 2021 | | 2021 |
| AI/ML IN ARCHITECTURE & ROBOTICS A KOTOV, I VUKOREP | | 2021 |
| AIAAF 19 Symposium Report I Vukorep, M Zwierzycki, B Baletic, P Nicholas, M Smigielska, M Gheorghe, ... INIK eV, 2020 | | 2020 |
