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Found 6 papers, 0 papers with code
Factor Importance Ranking and Selection using Total Indices
Factor importance measures the impact of each feature on output prediction accuracy.
Asset Bundling for Wind Power Forecasting
This approach effectively introduces an auxiliary learning task (predicting the bundle-level time series) to help the main learning tasks.
Optimal Sub-sampling to Boost Power of Kernel Sequential Change-point Detection
We present a novel scheme to boost detection power for kernel maximum mean discrepancy based sequential change-point detection procedures.
Risk-Aware Control and Optimization for High-Renewable Power Grids
The transition of the electrical power grid from fossil fuels to renewable sources of energy raises fundamental challenges to the market-clearing algorithms that drive its operations.
Uncertainty Quantification
Vocal Bursts Intensity Prediction
MAGI-X: Manifold-Constrained Gaussian Process Inference for Unknown System Dynamics
Ordinary differential equations (ODEs), commonly used to characterize the dynamic systems, are difficult to propose in closed-form for many complicated scientific applications, even with the help of domain expert.
An Infinite Hidden Markov Model With Similarity-Biased Transitions
We describe a generalization of the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) which is able to encode prior information that state transitions are more likely between "nearby" states.
