activity
20212026
most citedWiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data

3 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2026

BioDCASE: Active Learning for Bioacoustics

Ben McEwen, Rupa Kurinchi-Vendhan, Shiqi Zhang +3

Ecological monitoring increasingly relies on machine learning models, whose performance depends on the quality and quantity of labelled data. However, obtaining these labels is cos…

cs.LG2026

Finding Needles in the Haystack: Transductive Active Labeling in Ecology

Rupa Kurinchi-Vendhan, Sara Beery

Active learning is now standard practice in labeling ecological data, enabling ecologists to quickly process large volumes of field data to understand and monitor natural environme…

cs.CV2026

Seeing Through the PRISM: Compound & Controllable Restoration of Scientific Images

Rupa Kurinchi-Vendhan, Pratyusha Sharma, Antonio Torralba +1

Scientific and environmental imagery often suffer from complex mixtures of noise related to the sensor and the environment. Existing restoration methods typically remove one degrad…

cs.CV2025

INQUIRE-Search: Interactive Discovery in Large-Scale Biodiversity Databases

Edward Vendrow, Julia Chae, Rupa Kurinchi-Vendhan +10

Many ecological questions center on complex phenomena, such as species interactions, behaviors, phenology, and responses to disturbance, that are inherently difficult to observe an…

cs.CV2023

BenthIQ: a Transformer-Based Benthic Classification Model for Coral Restoration

Rupa Kurinchi-Vendhan, Drew Gray, Elijah Cole

Coral reefs are vital for marine biodiversity, coastal protection, and supporting human livelihoods globally. However, they are increasingly threatened by mass bleaching events, po…

cs.CV20213 cited

WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data

Rupa Kurinchi-Vendhan, Björn Lütjens, Ritwik Gupta +2

The transition to green energy grids depends on detailed wind and solar forecasts to optimize the siting and scheduling of renewable energy generation. Operational forecasts from n…