4 citations · 8 across the 3 of their papers we have counts for
5 papers
Implicit Regularization of Mini-Batch Training in Graph Neural Networks
Clement Wang, Antoine Vialle, Robin Vaysse +1
Mini-batch training of Graph Neural Networks (GNNs) is fundamentally different from training on i.i.d. data: sampling a subgraph alters the topology and introduces boundary effects…
Leveraging Multi-Temporal Sentinel 1 and 2 Satellite Data for Leaf Area Index Estimation With Deep Learning
Clement Wang, Antoine Debouchage, Valentin Goldité +2
The Leaf Area Index (LAI) is a critical parameter to understand ecosystem health and vegetation dynamics. In this paper, we propose a novel method for pixel-wise LAI prediction by…
Ai4Fapar: How artificial intelligence can help to forecast the seasonal earth observation signal
Filip Sabo, Martin Claverie, Michele Meroni +1
This paper investigated the potential of a multivariate Transformer model to forecast the temporal trajectory of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR…
Quantum Machine Learning for Remote Sensing: Exploring potential and challenges
Artur Miroszewski, Jakub Nalepa, Bertrand Le Saux +1
The industry of quantum technologies is rapidly expanding, offering promising opportunities for various scientific domains. Among these emerging technologies, Quantum Machine Learn…
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection
Fulvio Sanguigni, Mikolaj Czerkawski, Lorenzo Papa +2
The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observati…