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LMU Munich, Center for Machine Learning (MCML)
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Spectral learning unlocks $\mathcal{O}(d\log d)$ covariance estimation for dense Gaussian dependencies, outperforming prior methods in forecasting and prediction tasks.
Understanding the right types of uncertainty for dynamical systems could revolutionize how we model and predict complex behaviors in AI.
