5 papers
MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training
Lucia Gordon, Serge Belongie, Christian Igel +1
Recent research in geospatial machine learning demonstrates that models pretrained with self-supervised learning on Earth observation data can perform well on downstream tasks with…
Dynamic Framework for Collaborative Learning: Leveraging Advanced LLM with Adaptive Feedback Mechanisms
Hassam Tahir, Faizan Faisal, Fady Alnajjar +5
This paper presents a framework for integrating LLM into collaborative learning platforms to enhance student engagement, critical thinking, and inclusivity. The framework employs a…
Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas
Esther Rolf, Lucia Gordon, Milind Tambe +1
While advances in machine learning with satellite imagery (SatML) are facilitating environmental monitoring at a global scale, developing SatML models that are accurate and useful…
Multimodal Fusion Strategies for Mapping Biophysical Landscape Features
Lucia Gordon, Nico Lang, Catherine Ressijac +1
Multimodal aerial data are used to monitor natural systems, and machine learning can significantly accelerate the classification of landscape features within such imagery to benefi…
Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents
Lucia Gordon, Esther Rolf, Milind Tambe
Stochastic multi-agent multi-armed bandits typically assume that the rewards from each arm follow a fixed distribution, regardless of which agent pulls the arm. However, in many re…