Spaces:
Running
Running
| title: Multiscaler | |
| emoji: 🛰️ | |
| colorFrom: blue | |
| colorTo: yellow | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| short_description: Illustrating "Optimizing Multi-Scale Representations" | |
| # Overview | |
| This Shiny application allows users to visualize and explore results from the multi-scale representation approach described in the paper: | |
| Fucheng Warren Zhu, Connor T. Jerzak, Adel Daoud. Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Application to Two Anti-Poverty RCTs. Forthcoming in *Proceedings of the Fourth Conference on Causal Learning and Reasoning (CLeaR)*, 2025. | |
| The app focuses on how varying the scale of Earth Observation (EO) inputs can affect conditional average treatment effect (CATE) estimation. It provides both a 2D heatmap and a 3D surface plot, helping researchers analyze how model performance metrics change with different multi-scale representations. | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |