Personne
Robin Adrien Zbinden
Publications associées (5)
On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning
Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Lloyd Haydn Hughes
Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...
2024Measuring and shaping the nutritional environment via food sales logs: case studies of campus-wide food choice and a call to action
Robert West, Robin Adrien Zbinden, Kristina Gligoric
Although diets influence health and the environment, measuring and changing nutrition is challenging. Traditional measurement methods face challenges, and designing and conducting behavior-changing interventions is conceptually and logistically complicated ...
Frontiers Media Sa2024Exploring neural networks and their potential for species distribution modeling
Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Lloyd Haydn Hughes
Species distribution models (SDMs) relate species occurrence data with environmental variables and are used to understand and predict species distributions across landscapes. While some machine learning models have been adopted by the SDM community, recent ...
2023COBRA: Enhancing DNN Latency Prediction with Language Models trained on Source Code
With the recent developments of Deep Learning, having an accurate and device specific latency prediction for Deep Neural Networks (DNNs) has become important for both the manual and automatic design of efficient DNNs. Directly predicting the latency of DNN ...
2022A User Study of Perceived Carbon Footprint
Patrick Thiran, Matthias Grossglauser, Lucas Maystre, Victor Kristof, Robin Adrien Zbinden, Valentin Quelquejay-Leclère
We propose a statistical model to understand people's perception of their carbon footprint. Driven by the observation that few people think of CO2 impact in absolute terms, we design a system to probe people's perception from simple pairwise comparisons of ...
2019