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Robin Zbinden
Robin Zbinden
PhD student at EPFL
Verified email at epfl.ch
Title
Cited by
Cited by
Year
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
M Rußwurm, K Klemmer, E Rolf, R Zbinden, D Tuia
ICLR 2024, 2023
222023
Implementing and Experimenting with Diffusion Models for Text-to-Image Generation
R Zbinden
arXiv preprint arXiv:2209.10948, 2022
82022
On the Selection and Effectiveness of Pseudo-Absences for Species Distribution Modeling with Deep Learning
R Zbinden, N van Tiel, B Kellenberger, L Hughes, D Tuia
Ecological Informatics 81, 102623, 2024
62024
Imbalance-aware Presence-only Loss Function for Species Distribution Modeling
R Zbinden, N van Tiel, M Rußwurm, D Tuia
ICLR 2024 Workshop: Tackling Climate Change with Machine Learning, 2024
32024
Exploring the potential of neural networks for Species Distribution Modeling
R Zbinden, N van Tiel, B Kellenberger, L Hughes, D Tuia
ICLR 2023 Workshop: Tackling Climate Change with Machine Learning, 2023
2*2023
A User Study of Perceived Carbon Footprint
V Kristof, V Quelquejay-Leclère, R Zbinden, L Maystre, M Grossglauser, ...
NeurIPS 2019 Workshop: Tackling Climate Change with Machine Learning, 2019
22019
Multi-Scale and Multimodal Species Distribution Modeling
N van Tiel, R Zbinden, E Dalsasso, B Kellenberger, L Pellissier, D Tuia
arXiv preprint arXiv:2411.04016, 2024
2024
Measuring and Shaping the Nutritional Environment via Food Sales Logs: Case Studies of Campus-Wide Food Choice and a Call to Action
K Gligorić, R Zbinden, A Chiolero, E Kiciman, RW White, E Horvitz, ...
Frontiers in Nutrition 11, 1231070, 2024
2024
COBRA: Enhancing DNN Latency Prediction with Language Models trained on Source Code
R Zbinden, L Mauch, F Cardinaux
ICLR 2022 Workshop: Deep Learning for Code, 2022
2022
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