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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Monotonic Neural Networks 1
Published:
What was Monotonicity again?
portfolio
publications
Dynamic Modeling of P(VDF-TrFE-CTFE)-based Soft Actuators via Echo State Networks
Published in Proceedings of the 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2022
Echo state networks for dynamic modeling of electroactive polymer soft actuators.
Recommended citation: D'Anniballe, R., Erdmann, N., Selleri, G., & Carloni, R. (2022). "Dynamic Modeling of P(VDF-TrFE-CTFE)-based Soft Actuators via Echo State Networks." Proceedings of the 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), pp. 118–124.
Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle
Published in Proceedings of the 2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC), 2024
Probabilistic deep-learning forecasts of solar irradiance in the high-latitude Norwegian setting.
Recommended citation: Erdmann, N., Bentsen, L. Ø., Stenbro, R., Riise, H. N., Warakagoda, N., & Engelstad, P. (2024). "Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle." Proceedings of the 2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC), pp. 1599–1606.
Reinforcement Learning for Pollution Detection in a Randomized, Sparse and Nonstationary Environment with an Autonomous Underwater Vehicle
Published in arXiv preprint arXiv:2510.26347, 2025
Reinforcement learning for pollution detection with an autonomous underwater vehicle in sparse, nonstationary environments.
Recommended citation: Zieglmeier, S., Erdmann, N., & Warakagoda, N. D. (2025). "Reinforcement Learning for Pollution Detection in a Randomized, Sparse and Nonstationary Environment with an Autonomous Underwater Vehicle." arXiv preprint arXiv:2510.26347.
Multi-Horizon Time Series Forecasting of Non-Parametric CDFs with Deep Lattice Networks
Published in Proceedings of the 40th AAAI Conference on Artificial Intelligence, 2026
Forecasting full non-parametric predictive CDFs across multiple horizons using monotonic deep lattice networks.
Recommended citation: Erdmann, N., Bentsen, L., Stenbro, R., Riise, H. N., Warakagoda, N. D., & Engelstad, P. E. (2026). "Multi-Horizon Time Series Forecasting of Non-Parametric CDFs with Deep Lattice Networks." Proceedings of the 40th AAAI Conference on Artificial Intelligence.
Deep Learning Multihorizon Irradiance Nowcasting: A Comparative Evaluation of Three Methods for Leveraging Sky Images
Published in IEEE Journal of Photovoltaics, 2026
A comparative evaluation of three deep-learning methods for leveraging sky images in multi-horizon solar irradiance nowcasting.
Recommended citation: Eriksen, E. W., Nygård, M. M., Erdmann, N., & Riise, H. N. (2026). "Deep Learning Multihorizon Irradiance Nowcasting: A Comparative Evaluation of Three Methods for Leveraging Sky Images." IEEE Journal of Photovoltaics, 16(4), 594–604.
Estimating Lithium-Ion Battery State-of-Health with Monotonic Lattice Networks
Published in SSRN (preprint), 2026
Monotonic lattice networks for estimating lithium-ion battery state-of-health.
Recommended citation: Fordham, D., & Erdmann, N. (2026). "Estimating Lithium-Ion Battery State-of-Health with Monotonic Lattice Networks." SSRN preprint.
talks
Hierarchical Reinforcement Learning with AUVs
Published:
Hierarchical reinforcement learning for pollution detection with AUVs.
Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle
Published:
Best Poster Award for probabilistic solar irradiance forecasting at the Arctic Circle.
Forecasting Uncertainty with ML
Published:
On forecasting uncertainty and probabilistic forecasting.
Multi-Horizon Time Series Forecasting of Non-Parametric CDFs with Deep Lattice Networks
Published:
Conference presentation of the deep-lattice CDF forecasting work.
teaching
Teaching Assistant
Teaching assistant, University of Groningen, 2019
Led tutorial sessions, graded assignments and exams, and coordinated a group of other teaching assistants.
PhD Teaching Component
Lecturing, assignment design & supervision, University of Oslo, Department of Technology Systems, 2024
One of the four years of my PhD is contractually dedicated to teaching, alongside formal teaching education. Activities include holding lectures, designing assignments, and assisting with exams. This currently includes independent supervision of five Master’s thesis projects.