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• Learning and Combinatorial Optimization for Efficient Container Vessel Stowage Planning
  Learning and Combinatorial Optimization for Efficient Container Vessel Stowage Planningvan Twiller, J., 14 May 2025, 221 p.Research output: Theses › PhD thesis
• Don’t Get Too Excited - Eliciting Emotions in LLMs
  Don’t Get Too Excited - Eliciting Emotions in LLMsFazzi, G. F., Skoven Hinge, J., Heinrich, S. & Burelli, P., 2025, Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 9 p.Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Exploring Deep Learning Models for EEG Neural Decoding
  Exploring Deep Learning Models for EEG Neural DecodingDixen, L., Heinrich, S. & Burelli, P., 2025, International Symposium on Artificial Intelligence and Neuroscience. Springer, p. 162-175 13 p. (Lecture Notes in Computer Science).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Children’s expressed emotions during playful learning games
  Children’s expressed emotions during playful learning gamesVolden, T. V. S. & Burelli, P., 7 Oct 2024, European Conference on Game Based Learning. Vol. 18. 9 p.Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• PPSTOW: An End-to-End Deep Reinforcement Learning Model for Master Stowage Planning on Container Vessels
  PPSTOW: An End-to-End Deep Reinforcement Learning Model for Master Stowage Planning on Container Vesselsvan Twiller, J., Grbic, D. & Jensen, R. M., 30 Jun 2024.Research output: Contribution to conference - NOT published in proceeding or journal › Conference abstract for conference › Research › peer-review
• Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration
  Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art ExplorationMeyer, L. S., Engel Aaen, J., Tranberg, A. R., Kun, P., Freiberger, M., Risi, S. & Løvlie, A. S., 11 May 2024, Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration. p. 1-18 18 p. (ACM Annual Conference on Human Factors in Computing […]
• Introducing AI Experience: Games UX in the Age of Generative AI
  Introducing AI Experience: Games UX in the Age of Generative AIDrachen, A., Burelli, P., Kallabis, L. & Melhart, D., 2024, Report from Dagstuhl Seminar 24261.Research output: Conference Article in Proceeding or Book/Report chapter › Report chapter › Research
• Hades Again and Again: A Study on Frustration Tolerance, Physiology and Player Experience
  Hades Again and Again: A Study on Frustration Tolerance, Physiology and Player ExperienceFrost Jensen, M., Dixen, L. & Burelli, P., 2024, Lecture Notes in Computer Science: Proceedings of ACG 2023 . Springer, Vol. 14528. (Lecture Notes in Computer Science).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Modeling Face Emotion Perception from Naturalistic Face Viewing: Insights from Fixational Events and Gaze Strategies
  Modeling Face Emotion Perception from Naturalistic Face Viewing: Insights from Fixational Events and Gaze StrategiesSeikavandi, M. J., Barrett, M. J. & Burelli, P., 2024, Recent Advances in Deep Learning Applications: New Techniques and Practical Examples. Taylor & Francis, Vol. 1. Research output: Conference Article in Proceeding or Book/Report chapter › Book chapter › Research › […]
• Difficulty Modelling in Mobile Puzzle Games: An Empirical Study on Different Methods to Combine Player Analytics and Simulated Data
  Difficulty Modelling in Mobile Puzzle Games: An Empirical Study on Different Methods to Combine Player Analytics and Simulated DataKristensen, J. T. & Burelli, P., 2024, In: International Journal of Computer Games Technology. 14 p.Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
• Small, Safe LLMs for In-Game Generation
  Small, Safe LLMs for In-Game GenerationVeale, T., Burelli, P., Hoover, A. K., Liapis, A., Mountain, G. & Skubch, H., 2024, Report from Dagstuhl Seminar 24261. p. 206-208 Research output: Conference Article in Proceeding or Book/Report chapter › Report chapter › Research
• Deep Reinforcement Learning for Master Stowage Planning
  Deep Reinforcement Learning for Master Stowage Planningvan Twiller, J., Grbic, D. & Jensen, R. M., 2024, ODYSSEUS 2024: International Workshop on Freight Transportation and Logistics. 9th ed. Carmona, SpainResearch output: Conference Article in Proceeding or Book/Report chapter › Conference abstract in proceedings › Research › peer-review
• Bio-Inspired Approaches to Adaptive Artificial Agents
  Bio-Inspired Approaches to Adaptive Artificial AgentsWinther Pedersen, J., 23 Oct 2023, Copenhagen: IT University of Copenhagen. 225 p.Research output: Theses › PhD thesis
• Probabilistic Modeling for Game Content Creation and Adaption
  Probabilistic Modeling for Game Content Creation and AdaptionDuque, M. G., 1 Aug 2023, 1 ed. Copenhagen: IT-Universitetet i København. 152 p.Research output: Theses › PhD thesis
• CastNet: a systems-level sequence evolution simulator
  CastNet: a systems-level sequence evolution simulatorRivera-Rivera, C. J. & Grbic, D., 12 Jun 2023, In: BMC Bioinformatics. 8 p., 247.Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
• Procedurally generating rules to adapt difficulty for narrative puzzle games
  Procedurally generating rules to adapt difficulty for narrative puzzle gamesVolden, T., Grbic, D. & Burelli, P., 2023, Proceedings of the IEEE Conference on Game. IEEE, p. 1-4 4 p. (Proceedings of the 2023 IEEE conference on Games).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
  Towards Self-Assembling Artificial Neural Networks through Neural Developmental ProgramsNajarro, E., Risi, S. & Sudhakaran, S., 2023, In: Artificial Life Conference Proceedings .Research output: Journal Article or Conference Article in Journal › Conference article › Research › peer-review
• Investigating the Uncanny Valley Phenomenon Through the Temporal Dynamics of Neural Responses to Virtual Characters
  Investigating the Uncanny Valley Phenomenon Through the Temporal Dynamics of Neural Responses to Virtual CharactersGorlini, C., Dixen, L. & Burelli, P., 2023, Proceedings of the IEEE Conference on Game. IEEE, (Proceedings of the 2023 IEEE conference on Games).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Investigating Perceived and Mechanical Challenge in Games Through Cognitive Activity
  Investigating Perceived and Mechanical Challenge in Games Through Cognitive ActivityHegedues, C., Dias Constantino, J. P., Dixen, L. & Burelli, P., 2023, Proceedings of the IEEE Conference on Game. IEEE, (Proceedings of the 2023 IEEE conference on Games).Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review
• Minimal Neural Network Models for Permutation Invariant Agents
  Minimal Neural Network Models for Permutation Invariant AgentsWinther Pedersen, J. & Risi, S., 9 Jul 2022.Research output: Contribution to conference - NOT published in proceeding or journal › Paper › Research › peer-review