arXiv:2606. 08484v1 Announce Type: cross Abstract: Joint Species Distribution Modeling (JSDM) is a key enabler for biodiversity monitoring and conservation planning.
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The paper introduces SAGE, a Sampling‑Aware Global Evaluation benchmark for species distribution modeling that uses GBIF records for training and sPlotOpen vegetation plots for presence‑absence evaluation across 5,771 plant species. It groups species by sampling effort and relative prevalence to assess how well single‑species and multi‑species deep‑learning SDMs perform under different data conditions. The study finds that Random Forests and DeepSDMs perform best overall, with DeepSDMs excelling for infrequently recorded species only when bias‑correction techniques are applied.
arXiv:2607. 21088v1 Announce Type: new Abstract: Deep subspace clustering plays a critical role in applications involving multivariate spatiotemporal data, such as sea ice monitoring, disease spread analysis, and tracking neuro-degeneration over time.
arXiv:2609.09705v1 Announce Type: new Abstract: Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Un...
arXiv:2606. 08046v1 Announce Type: new Abstract: We present OSMGraphCLIP, a CLIP-style geospatial representation model that learns global location embeddings from freely available OpenStreetMap (OSM) data.
arXiv:2608. 06402v1 Announce Type: new Abstract: Community detection is a fundamental task in graph analytics that aims to identify cohesive groups of entities with similar behaviors or interests.
arXiv:2609.26855v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) models multi-table databases as heterogeneous temporal graphs, and graph transformers currently achieve state-of-the-a...