2026
MIAM: Modality Imbalance-Aware Masking for Multimodal Ecological Applications
ICLR 2026poster
Multimodal learning is crucial for ecological applications, which rely on heterogeneous data sources (e.g., satellite imagery, environmental time series, tabular predictors, bioacoustics) but often suffer from incomplete data across and within modalities (e.g., unavailable satellite image due to clo…