3 papers
physics.ao-ph2025
Calibrating Geophysical Predictions under Constrained Probabilistic Distributions
Zhewen Hou, Jiajin Sun, Subashree Venkatasubramanian +3
Machine learning (ML) has shown significant promise in studying complex geophysical dynamical systems, including turbulence and climate processes. Such systems often display sensit…
cs.LG2025
Machine Learning Workflows in Climate Modeling: Design Patterns and Insights from Case Studies
Tian Zheng, Subashree Venkatasubramanian, Shuolin Li +5
Machine learning has been increasingly applied in climate modeling on system emulation acceleration, data-driven parameter inference, forecasting, and knowledge discovery, addressi…
cs.LG2024
Variational Encoder-Decoders for Learning Latent Representations of Physical Systems
Subashree Venkatasubramanian, David A. Barajas-Solano
We present a deep-learning Variational Encoder-Decoder (VED) framework for learning data-driven low-dimensional representations of the relationship between high-dimensional paramet…