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cs.LG2024
Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatments
Ziyang Jiang, Zach Calhoun, Yiling Liu +2
Causal reasoning is often challenging with spatial data, particularly when handling high-dimensional inputs. To address this, we propose a neural network (NN) based framework integ…
cs.LG2024★ 1 cited
Augmenting Ground-Level PM2.5 Prediction via Kriging-Based Pseudo-Label Generation
Lei Duan, Ziyang Jiang, David Carlson
Fusing abundant satellite data with sparse ground measurements constitutes a major challenge in climate modeling. To address this, we propose a strategy to augment the training dat…