4th ICLR Workshop on Machine Learning for Remote Sensing
Abstract
Machine Learning for Remote Sensing (ML4RS) has rapidly evolved into a vibrant research area. Remote sensing provides the ML community with an unparalleled source of multimodal, spatiotemporal data—challenging algorithms to learn from vast, heterogeneous, and dynamically changing observations of our planet. Building on the success of ML4RS workshops at ICLR 2023-2025, the 4th ICLR Workshop on Machine Learning for Remote Sensing will focus on bridging the persistent gap between publication and practice. Our theme, “ML4RS: From Publication to Practice,” aims to connect research innovations with their real-world deployment. This year’s workshop introduces two new elements: an interactive tutorials track and an opportunity for research track papers to be published in journal proceedings. Alongside invited provocations and debates on “Foundation Models in ML4RS: Are We There Yet?”, our program highlights contributions across key challenges in the field—including data efficiency, interpretability, benchmarking, and global versus local model design. Building on ML4RS’s tradition of highlighting speakers and challenges related to the ICLR host location, ML4RS 2026 emphasizes local engagement with Brazil’s dynamic remote sensing and ML communities while continuing to cultivate a diverse, international ecosystem of researchers, practitioners, and end-users. By bridging methodological innovation and practical application, ML4RS 2026 aims to advance the scientific and societal impact of machine learning for Earth observation.