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Found 3 papers, 2 papers with code
Copula Conformal Prediction for Multi-step Time Series Forecasting
Accurate uncertainty measurement is a key step to building robust and reliable machine learning systems.
Conformal Methods for Quantifying Uncertainty in Spatiotemporal Data: A Survey
Machine learning methods are increasingly widely used in high-risk settings such as healthcare, transportation, and finance.
Probabilistic Symmetry for Multi-Agent Dynamics
We propose a novel deep dynamics model, Probabilistic Equivariant Continuous COnvolution (PECCO) for probabilistic prediction of multi-agent trajectories.
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