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Found 4 papers, 3 papers with code
Deep Gaussian Covariance Network with Trajectory Sampling for Data-Efficient Policy Search
We compare trajectory sampling with density-based approximation for uncertainty propagation using three different probabilistic world models; Gaussian processes, Bayesian neural networks, and DGCNs.
Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals
The lack of anomaly detection methods during mechanized tunnelling can cause financial loss and deficits in drilling time.
Gradient and Uncertainty Enhanced Sequential Sampling for Global Fit
Therefore, we compared our proposed strategy to 9 adaptive sampling strategies for global surrogate modeling, based on 26 different 1 to 8-dimensional deterministic benchmarks functions.
Local Latin Hypercube Refinement for Multi-objective Design Uncertainty Optimization
Optimizing the reliability and the robustness of a design is important but often unaffordable due to high sample requirements.
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