paper
2025
Hybrid physics-ML & parameterization
Climate emulation New model or method
Physics-informed / physics-constrainedFudan University (FuXi)Nanjing University of Information Science & Technology (NUIST) Conference
2025-01-01
047
Jan 2025
Jiyang Xia, Feng-Hua Ling, Z. Li et al.
Advances in Neural Information Processing Systems 38
Fudan University (FuXi), Nanjing University of Information Science & Technology (NUIST)
Proposes a physics-guided learning approach for urban surface-atmosphere interactions to model urban climate dynamics; no abstract was provided, so this relies on the title.
Hybrid physics-ML & parameterization
Learning Urban Climate Dynamics via Physics-Guided Urban Surface-Atmosphere Interactions
In one sentence. Proposes a physics-guided learning approach for urban surface-atmosphere interactions to model urban climate dynamics; no abstract was provided, so this relies on the title.
Labels
- Topic
- Hybrid physics-ML & parameterization, Climate emulation
- Type
- New model or method
- Method
- Physics-informed / physics-constrained
- Domain
- Local / station
- Status
- Research
- Identifiers
- DOI:10.52202/085713-4194 OpenAlex:W7196943346
- Added
- 2026-10-22
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