Online generalised predictive coding (ODEM) tracks latent states in nonlinear and chaotic generative models by separating temporal scales for fast Bayesian belief updating and slow parameter learning.
Dropout as a bayesian approximation
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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The work introduces WaLeF/FIDLAr for flood forecasting, CoDiCast for probabilistic weather, and Hypercube-RAG for explainable environmental QA, claiming superior accuracy, efficiency, and interpretability over baselines.
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Online Generalised Predictive Coding
Online generalised predictive coding (ODEM) tracks latent states in nonlinear and chaotic generative models by separating temporal scales for fast Bayesian belief updating and slow parameter learning.
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Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems
The work introduces WaLeF/FIDLAr for flood forecasting, CoDiCast for probabilistic weather, and Hypercube-RAG for explainable environmental QA, claiming superior accuracy, efficiency, and interpretability over baselines.