Alan Lahoud
Alan Lahoud Position: Doctoral Student School/office: School of Science and TechnologyEmail: YWxhbi5sYWhvdWQ7b3J1LnNl
Phone: +46 19 301226
Room: T1209
Research subject
Research environments
About Alan Lahoud
Alan is a Ph.D. student in the field of Computer Science and is affiliated to the WASP research program. Alan's project has a collaboration with H&M Group as part of the CoAIRob school. Alan is a member of the Adaptive and Interpretable Learning Systems (AILS) lab. His research interests include Probabilistic Machine Learning and their applications to Optimization Problems.
Research groups
Publications
Conference papers |
Conference papers
- Lahoud, A. A. , Schaffernicht, E. & Stork, J. A. (2024). Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks. In: Michael Wand; Kristína Malinovská; Jürgen Schmidhuber; Igor V. Tetko, Artificial Neural Networks and Machine Learning – ICANN 2024 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part I. Paper presented at 33rd International Conference on Artificial Neural Networks and Machine Learning (ICANN 2024), Lugano, Switzerland, September 17-20, 2024. (pp. 147-162). Springer. [BibTeX]