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View article: Gradient-free Importance Sampling Scheme for Efficient Reliability Estimation
Gradient-free Importance Sampling Scheme for Efficient Reliability Estimation Open
This work presents a novel gradient-free importance sampling-based framework for precisely and efficiently estimating rare event probabilities, often encountered in reliability analyses of engineering systems. The approach is formulated ar…
View article: A Direct Importance Sampling-based Framework for Rare Event Uncertainty Quantification in Non-Gaussian Spaces
A Direct Importance Sampling-based Framework for Rare Event Uncertainty Quantification in Non-Gaussian Spaces Open
This work introduces a novel framework for precisely and efficiently estimating rare event probabilities in complex, high-dimensional non-Gaussian spaces, building on our foundational Approximate Sampling Target with Post-processing Adjust…
View article: WildGraph: Realistic Graph-based Trajectory Generation for Wildlife
WildGraph: Realistic Graph-based Trajectory Generation for Wildlife Open
Trajectory generation is an important task in movement studies; it circumvents the privacy, ethical, and technical challenges of collecting real trajectories from the target population. In particular, real trajectories in the wildlife doma…
View article: WildGEN: Long-horizon Trajectory Generation for Wildlife
WildGEN: Long-horizon Trajectory Generation for Wildlife Open
Trajectory generation is an important concern in pedestrian, vehicle, and wildlife movement studies. Generated trajectories help enrich the training corpus in relation to deep learning applications, and may be used to facilitate simulation…
View article: Hamiltonian MCMC methods for estimating rare events probabilities in high-dimensional problems
Hamiltonian MCMC methods for estimating rare events probabilities in high-dimensional problems Open
Accurate and efficient estimation of rare events probabilities is of significant importance, since often the occurrences of such events have widespread impacts. The focus in this work is on precisely quantifying these probabilities, often …