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Alexander Shepard

5 accepted papers

2025

Feedforward Few-shot Species Range Estimation

ICML 2025poster

Knowing where a particular species can or cannot be found on Earth is crucial for ecological research and conservation efforts. By mapping the spatial ranges of all species, we would obtain deeper insights into how global biodiversity is affected by climate change and habitat loss. However, accurat…

Cited by 0SourcePDFScholar
2024

Combining Observational Data and Language for Species Range Estimation

NeurIPS 2024poster

Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management. However, traditional SRMs rely on the availability of environmental covariates and high-quality observational data, both of which can be challenging to obtain due to g…

2024

INQUIRE: A Natural World Text-to-Image Retrieval Benchmark

NeurIPS 2024poster

We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24), a new dataset of five million natural world images, along with 250 expert-level retrieval queries. These queries are…

2023

Spatial Implicit Neural Representations for Global-Scale Species Mapping

ICML 2023poster

Estimating the geographical range of a species from sparse observations is a challenging and important geospatial prediction problem. Given a set of locations where a species has been observed, the goal is to build a model to predict whether the species is present or absent at any location. This pro…