Workshop paper track
4-page short papers describing new and ongoing/in-progress research; double-blind review; unlimited references; optional appendix; non-archival; dual submission allowed where permitted.
Machine Learning/CORE Unranked
ML4RS @ ICLR 2026
4th ICLR Workshop on Machine Learning for Remote Sensing (Main Track)
The ML4RS @ ICLR 2026 workshop promotes trans-disciplinary research at the intersection of machine learning and remote sensing, with a special theme of 'publication to practice' aimed at bridging the gap between research and real-world applications. It focuses on advancing methodologies and applications for addressing global challenges like climate change, biodiversity, and food security through innovative ML approaches tailored to remote sensing data.
Key deadlines
Verified September 9, 2026Full paper
February 7, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
February 7, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Tiny paper track
2-page papers presenting focused contributions such as modest experimental results, fresh perspectives, theoretical insights, or new ideas; unlimited references; no appendices; encourages participation from students and newcomers; non-archival; dual submission allowed where permitted.
Tutorials track
Up to 4-page papers detailing tutorials for models, code libraries, datasets, or benchmarks; single-blind review; expected to include executable code (e.g., Colab/Jupyter notebooks); accepted submissions must record a 15-minute video tutorial; non-archival.
Research areas in scope
01
Research Topics
Foundation models: capturing spectral, spatial, and temporal nuances in unlabeled satellite dataActive learning & annotation efficiency: maximizing model performance with limited labelingImperfect evaluation data: assessing model quality with sparse or uncertain labelsInterpretability & generalization: using geospatial priors and physical models for transparency and robustnessBenchmarking & impact: developing metrics that reflect real-world impact and enable fair comparisonAccessibility & efficiency: democratizing ML4RS through distributed, low-cost trainingLocal vs. global models: identifying scopes for transfer between modelsPrecomputed embeddings: effectively using precomputed embeddings from foundation models
Policies worth checking twice
- Workshop paper track submissions must be double-blind; no author names or identifying links (e.g., GitHub) allowed.
- Page limits do not include references, which are unlimited.
- Workshop papers may include an optional appendix that does not count toward the page limit.
- Tiny paper track does not allow appendices.
- Tutorials track is single-blind; anonymization is not required.
- AI-generated papers are explicitly not allowed for the tiny paper and workshop paper tracks.
- Dual submission is allowed where permitted by third parties.
- Authors of workshop papers may opt to have their 4-page submissions evaluated for the GRSL special stream, which involves an additional review phase and publication fees.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026