Publications

• Lightweight Probabilistic Downscaling from a Deterministic Base Model
  Joseph McLean, Tiffany Vlaar, Sigrid Passano Hellan and Linus Ericsson
  To be presented at the Workshop on Advances in Representation Learning for Earth Observation at NeurIPS 2026.
• Bayesian Optimisation Against Climate Change: Applications and Benchmarks
  Sigrid Passano Hellan, Christopher Lucas and Nigel Goddard
  Lecture Notes in Computer Science, 2026
  Presented at the 2025 Learning and Intelligent Optimization Conference. Code is here.
• Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimization
  Sigrid Passano Hellan, Huibin Shen, François-Xavier Aubet, David Salinas and Aaron Klein
  Proceedings of Machine Learning Research, 2025
  Presented at the AutoML 2025 conference. Code is here.
• Hyperparameter Selection in Continual Learning
  Thomas L. Lee, Sigrid Passano Hellan, Linus Ericsson, Elliot J. Crowley and Amos Storkey
  Presented at the CoLLAs 2024 conference workshop track.
• Data-driven Prior Learning for Bayesian Optimisation
  Sigrid Passano Hellan, Christopher Lucas and Nigel Goddard
  Presented at the Adaptive Experimental Design and Active Learning in the Real World workshop at NeurIPS 2023. Code is here.
• Bayesian Optimisation for Active Monitoring of Air Pollution
  Sigrid Passano Hellan, Christopher Lucas and Nigel Goddard
  Proceedings of the AAAI Conference on Artificial Intelligence, 2022
  Presented at AAAI 2022. Code available here. Poster available here.
• Optimising Placement of Pollution Sensors in Windy Environments
  Sigrid Passano Hellan, Christopher Lucas and Nigel Goddard
  Presented at the AI for Earth Sciences Workshop at NeurIPS 2020. Check out the video here.

Tutorials

• Using Syne Tune for Transfer Learning contributed to the official Syne Tune documentation.
• Derivatives and Gaussian Processes published on the CDT in Data Science blog.

Talks

• How unlikely was the storm Hans? Reusing extended range forecasts to anticipate unprecedented extremes. EGU 2026.
• Hyperparameter tuning, Bayesian optimisation and applications related to climate change. Learning Machines seminar. September 2025.
• Machine learning for weather forecasting — An introduction. Contribution to lecture at the CATER 2024 summer school on Transdisciplinary Climate Risk and Action. October 2024.
• Affordable Bayesian Optimisation Contributed talk at the First Edinburgh Workshop on Affordable Machine Learning. June 2023.

Blog posts

• Spotting an Air Pollution Sensor in the Wild, 12 May 23.

PhD Thesis

• Bayesian Optimisation & Priors:
  Improving Air Pollution Monitoring and Hyperparameter Optimisation
  Sigrid Passano Hellan, University of Edinburgh, 2024
  Supervised by Nigel Goddard and Christopher Lucas.

Teaching material

• BCCR Training Programme in Machine Learning
  Teaching material developed for an evening course at the University of Bergen, and for machine learning training at the Bjerknes Centre for Climate Research. Developed with Robin Guillaume-Castel.

Google Scholar profile.