conference paper Hans Harder author 98879 Abhijeet Vishwasrao author Luca Guastoni author Ricardo Vinuesa author Sebastian Peitz author 474270000-0002-3389-793X GauravSukhatme editor LarsLindemann editor StephenTu editor AdamWierman editor NikolayAtanasov editor 655 department PMLR2026 eng ownown-conferenceerc 10.48550/arXiv.2511.04641 3311601–1619 Harder, H., Vishwasrao, A., Guastoni, L., Vinuesa, R., &#38; Peitz, S. (2026). Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In G. Sukhatme, L. Lindemann, S. Tu, A. Wierman, &#38; N. Atanasov (Eds.), <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i> (Vol. 331, pp. 1601–1619). PMLR. <a href="https://doi.org/10.48550/arXiv.2511.04641">https://doi.org/10.48550/arXiv.2511.04641</a> H. Harder, A. Vishwasrao, L. Guastoni, R. Vinuesa, and S. Peitz, “Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems,” in <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, 2026, vol. 331, pp. 1601–1619, doi: <a href="https://doi.org/10.48550/arXiv.2511.04641">10.48550/arXiv.2511.04641</a>. H. Harder, A. Vishwasrao, L. Guastoni, R. Vinuesa, S. Peitz, in: G. Sukhatme, L. Lindemann, S. Tu, A. Wierman, N. Atanasov (Eds.), Proceedings of The 8th Annual Learning for Dynamics and Control Conference, PMLR, 2026, pp. 1601–1619. Harder, Hans, Abhijeet Vishwasrao, Luca Guastoni, Ricardo Vinuesa, and Sebastian Peitz. “Efficient Probabilistic Surrogate Modeling Techniques for Partially-Observed Large-Scale Dynamical Systems.” In <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, edited by Gaurav Sukhatme, Lars Lindemann, Stephen Tu, Adam Wierman, and Nikolay Atanasov, 331:1601–1619. Proceedings of Machine Learning Research. PMLR, 2026. <a href="https://doi.org/10.48550/arXiv.2511.04641">https://doi.org/10.48550/arXiv.2511.04641</a>. Harder, Hans, et al. “Efficient Probabilistic Surrogate Modeling Techniques for Partially-Observed Large-Scale Dynamical Systems.” <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, edited by Gaurav Sukhatme et al., vol. 331, PMLR, 2026, pp. 1601–1619, doi:<a href="https://doi.org/10.48550/arXiv.2511.04641">10.48550/arXiv.2511.04641</a>. Harder H, Vishwasrao A, Guastoni L, Vinuesa R, Peitz S. Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In: Sukhatme G, Lindemann L, Tu S, Wierman A, Atanasov N, eds. <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>. Vol 331. Proceedings of Machine Learning Research. PMLR; 2026:1601–1619. doi:<a href="https://doi.org/10.48550/arXiv.2511.04641">10.48550/arXiv.2511.04641</a> @inproceedings{Harder_Vishwasrao_Guastoni_Vinuesa_Peitz_2026, series={Proceedings of Machine Learning Research}, title={Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems}, volume={331}, DOI={<a href="https://doi.org/10.48550/arXiv.2511.04641">10.48550/arXiv.2511.04641</a>}, booktitle={Proceedings of The 8th Annual Learning for Dynamics and Control Conference}, publisher={PMLR}, author={Harder, Hans and Vishwasrao, Abhijeet and Guastoni, Luca and Vinuesa, Ricardo and Peitz, Sebastian}, editor={Sukhatme, Gaurav and Lindemann, Lars and Tu, Stephen and Wierman, Adam and Atanasov, Nikolay}, year={2026}, pages={1601–1619}, collection={Proceedings of Machine Learning Research} } 672992026-10-01T11:51:57Z2026-10-01T11:52:48Z