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Found 5 papers, 5 papers with code
High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery
Accurate estimation of thermospheric density is critical for precise modeling of satellite drag forces in low Earth orbit (LEO).
BatchGFN: Generative Flow Networks for Batch Active Learning
We introduce BatchGFN -- a novel approach for pool-based active learning that uses generative flow networks to sample sets of data points proportional to a batch reward.
Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels
Automated planetary transit detection has become vital to prioritize candidates for expert analysis given the scale of modern telescopic surveys.
Multi-Modal Fusion by Meta-Initialization
In this work, we propose an extension to the Model-Agnostic Meta-Learning algorithm (MAML), which allows the model to adapt using auxiliary information as well as task experience.
Materials Graph Transformer predicts the outcomes of inorganic reactions with reliable uncertainties
A common bottleneck for materials discovery is synthesis.
Computational Physics Materials Science
