Traditional machine learning and deep learning techniques rely on correlation-based learning, often failing to distinguish spurious associations from true causal relationships, …
Traditional machine learning and deep learning techniques rely on correlation-based learning, often failing to distinguish spurious associations from true causal relationships, …
Causal modeling offers a principled foundation for uncovering stable, invariant relationships in time-series data, thereby improving robustness and generalization under …
We investigate the impact of ocean data assimilation using the Ensemble Adjustment Kalman Filter (EAKF) from the Data Assimilation Research Testbed (DART) on the oceanic and …
In the tropical Pacific, weak ventilation and intense microbial respiration at depth give rise to a low dissolved oxygen (O2) environment that is thought to be ventilated primarily …
Given coarser-resolution projections from global climate models or satellite data, the downscaling problem aims to estimate finer-resolution regional climate data, capturing …
The Greenland Ice Sheet (GrIS) has emerged as a significant contributor to global sea level rise, primarily due to increased meltwater runoff. Supraglacial lakes, which form on the …
