Selected publications

MIAM: Modality Imbalance-Aware Masking for Multimodal Ecological Applications

Robin Zbinden*, Wesley Monteith-Finas*, Gencer Sumbul, Nina van Tiel, Chiara Vanalli, Devis Tuia
ICLR (2026)
🌐 Webpage · 📄 Paper · 💻 Code · 💽 Data · 🏞️ Poster · 🎬 Video

MaskSDM with Shapley values to improve flexibility, robustness and explainability in species distribution modelling

Robin Zbinden, Nina van Tiel, Gencer Sumbul, Chiara Vanalli, Benjamin Kellenberger, Devis Tuia
Methods in Ecology and Evolution (2025)
🌐 Webpage · 📄 Paper · 💻 Code · 💽 Data

CISO: Species Distribution Modeling Conditioned on Incomplete Species Observations

Hager Radi Abdelwahed*, Mélisande Teng*, Robin Zbinden*, Laura Pollock, Hugo Larochelle, Devis Tuia, David Rolnick
Methods in Ecology and Evolution (2026)
🌐 Webpage · 📄 Paper · 💻 Code · 💽 Data · 🏞️ Poster

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks

Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia
ICLR (2024), ✨spotlight (top 5%)✨
🌐 Webpage · 📄 Paper · 💻 Code · 🏞️ Poster · 🎬 Video

GeoFAR: Geography-Informed Frequency-Aware Super-Resolution for Climate Data

Chang Xu, Gencer Sumbul, Li Mi, Robin Zbinden, Devis Tuia
ICLR (2026)
🌐 Webpage · 📄 Paper · 💻 Code · 🏞️ Poster · 🎬 Video

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Robin Zbinden, Nina van Tiel, Benjamin Kellenberger, Lloyd Hughes, Devis Tuia
Ecological Informatics (2024)
🌐 Webpage · 📄 Paper · 💻 Code

All publications

Multi-scale neural networks enhance species distribution modelling across predictors and taxonomic groups

Nina van Tiel, Robin Zbinden, Chiara Vanalli, Benjamin Kellenberger, Loic Pellissier, Devis Tuia
Ecological Informatics (2026)
📄 Paper · 💻 Code

MIAM: Modality Imbalance-Aware Masking for Multimodal Ecological Applications

GeoFAR: Geography-Informed Frequency-Aware Super-Resolution for Climate Data

Chang Xu, Gencer Sumbul, Li Mi, Robin Zbinden, Devis Tuia
ICLR (2026)
🌐 Webpage · 📄 Paper · 💻 Code · 🏞️ Poster · 🎬 Video

CISO: Species Distribution Modeling Conditioned on Incomplete Species Observations

Seasonal modeling of monarch butterfly migration

Migrating in a warming world: A deep learning approach to predict pan-American seasonal shifts in the monarch butterfly niche

Chiara Vanalli, Robin Zbinden, Nina van Tiel, Devis Tuia
Global Change Biology (2026)
📄 Paper · 💻 Code · 💽 Data · 🏞️ Poster

MaskSDM with Shapley values to improve flexibility, robustness and explainability in species distribution modelling

Multi-scale and Multimodal Species Distribution Modeling

Nina van Tiel, Robin Zbinden, Emanuele Dalsasso, Benjamin Kellenberger, Loïc Pellissier, Devis Tuia
ECCV Workshop: Computer Vision for Ecology (2024)
📄 Paper · 💻 Code

MaskSDM: Adaptive Species Distribution Modeling Through Data Masking

Robin Zbinden, Nina van Tiel, Gencer Sumbul, Benjamin Kellenberger, Devis Tuia
ECCV Workshop: Computer Vision for Ecology (2024)
📄 Paper · 🏞️ Poster

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Robin Zbinden, Nina van Tiel, Benjamin Kellenberger, Lloyd Hughes, Devis Tuia
Ecological Informatics (2024)
🌐 Webpage · 📄 Paper · 💻 Code

Imbalance-aware Presence-only Loss Function for Species Distribution Modeling

Robin Zbinden, Nina van Tiel, Marc Rußwurm, Devis Tuia
ICLR Workshop: Tackling Climate Change with Machine Learning (2024)
📄 Paper · 📊 Slides · 🏞️ Poster · 🎬 Video

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks

Measuring and Shaping the Nutritional Environment via Food Sales Logs: Case Studies of Campus-Wide Food Choice and a Call to Action

Kristina Gligorić, Robin Zbinden, Arnaud Chiolero, Emre Kiciman, Ryen W White, Eric Horvitz, Robert West
Frontiers in Nutrition (2024)
📄 Paper

Exploring the potential of neural networks for Species Distribution Modeling

Robin Zbinden*, Nina van Tiel*, Benjamin Kellenberger, Lloyd Hughes, Devis Tuia
ICLR Workshop: Tackling Climate Change with Machine Learning (2023)
📄 Paper · 🏞️ Poster

COBRA: Enhancing DNN Latency Prediction with Language Models trained on Source Code

Robin Zbinden*, Lukas Mauch*, Fabien Cardinaux
ICLR Workshop: Deep Learning for Code (2022)
📄 Paper · 🏞️ Poster

A User Study of Perceived Carbon Footprint

Victor Kristof, Valentin Quelquejay, Robin Zbinden, Lucas Maystre, Matthias Grossglauser, Patrick Thiran
NeurIPS Workshop: Tackling Climate Change with Machine Learning (2019)
📄 Paper · 📊 Slides · 🏞️ Poster · 🖥️ Platform