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Notes on transfer learning
2 notes
MarsCast: Transfer Learning of AI Weather Foundation Models to Planetary Atmospheres
Researchers adapted the GraphCast graph neural network weather forecasting model to Mars, achieving accurate predictions of current conditions with zero-shot training. Fine-tuning improved forecasts by capturing…
ASALT: Adaptive State Alignment for Lateral Transfer in Multi-agent Reinforcement Learning
The paper introduces ASALT, a method for multi-agent reinforcement learning (MARL) that allows for knowledge transfer between source and target domains even if the state space dimensions do not match. ASALT uses…
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