arXiv:2606. 19138v1 Announce Type: new Abstract: Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based extensions typically learn spatial structure purely from data, even in settings where a directed graph structure is known a priori.
By Michael Detzel, Gabriel Nobis, Kristiyan Blagov, Juri Schubert, Jackie Ma, Wojciech Samek
arXiv:2608. 08689v1 Announce Type: new Abstract: The state evolution of a complex system arises jointly from object laws, relational propagation, domain conservation, and unmodeled error.
By Wei Wang, Yaosen Chen, Han Yang, Yuegen Liu, Mingli Luo, Xinxin Jiao, Xuming Wen, Ming Liu
arXiv:2606. 31804v1 Announce Type: new Abstract: Accurate energy demand forecasting is essential for the reliable operation and planning of modern sustainable energy systems.
By Keivan Faghih Niresi, Alice Cicirello, Olga Fink
arXiv:2505. 23863v3 Announce Type: replace-cross Abstract: Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dynamics, yet direct experimentation and intervention in such systems are often infeasible.
By Chang Liu, Bohao Zhao, Jingtao Ding, Huandong Wang, Yong Li
arXiv:2606. 17070v1 Announce Type: cross Abstract: Accurate oceanic forecasting is critical for climate monitoring and disaster early warning.
By Qinghui Chen, Zekai Zhang, Hailong Liu, Jinglin Zhang, Cong Bai
arXiv:2606. 31248v1 Announce Type: cross Abstract: Kilometer-scale convection shapes precipitation extremes, tropical organization, and cloud feedbacks, but most global atmospheric models approximate these processes at 25-100 km resolution.
By Zeyuan Hu, Akshay Subramaniam, Noel Keen, Tao Ge, Jaideep Pathak, Mohammad Shoaib Abbas, Suman Ravuri, Karthik Kashinath, Naser Mahfouz, Peter Caldwell, Mike Pritchard, Noah Brenowitz