Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 50 for “"efficient sampling"”.
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Efficient sampling for determinantal point processes
… size-k subsets. In this thesis, we address efficient sampling algorithms and applications of (k-DPP). First, we propose a new method to approximately sample from k-Dpps. Our method takes advantage of the diversity property of subsets sampled from a DPP. It proceeds in two stages: first, it …
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Efficient Sampling Methods for Forest Inventories and Growth Projections
… With time and costs constraints, appropriate sampling designs and models are required to perform the inventory efficiently, as well as to obtain reliable estimates for the variables needed to make projections. In this dissertation research, a simulation study was conducted to extensively …
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Efficient Sampling Methods of, by, and for Stochastic Dynamical Systems
… for dynamical systems to create methods for efficient rare event simulation in nonlinear SDEs. Our approach exploits the relationship between the stochastic Koopman operator and the Kolmogorov backward equation to derive optimal importance sampling and multilevel splitting estimators. By …
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Efficient sampling of protein conformational dynamics and prediction of mutation effects.
… method, based on the idea of maximum-caliber, to efficiently predict the changes in protein folding behavior upon mutation. Next, we explore the accuracy of different MSM estimators applied to trajectory data obtained by adaptive seeding, in which new rounds of short MD simulations are collected …
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Efficient Sampling Plans for Control Charts When Monitoring an Autocorrelated Process
… autocorrelation on the performances of various sampling plans for control charts in detecting special causes that may produce sustained or transient shifts in the process mean and/or variance. Observations from the process are modeled as a first-order autoregressive process plus a random error. …
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Design and implementation of discrete-time filters for efficient sampling rate conversion
… both classes of structures are discussed, and an efficient class of structures is proposed. The Generalized Transposition Theorem is also reviewed to demonstrate that an efficient downsampling structure also implies an equally efficient, closely-related upsampling structure. Techniques are …
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More Efficient Sampling for Bayesian Calibration of Computationally Expensive Hydrologic and Environmental Simulation Models
In recent years, interest in Bayesian calibration of hydrologic and environmental simulation (HE) models has been growing. The Bayesian approach allows for making statistical inference on unknown parameters and has proved to be an effective method to treat the estimation uncertainty arising from …
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Learning Diffusion Models to Enable Efficient Sampling for Task and Motion Planning on a Panda Robot
… refined into low-level continuous transitions by sampling controller parameters associated with each action. Efficiently sampling these parameters remains a significant challenge, as exhaustive searches often become computational bottlenecks, especially for tasks requiring complex or multimodal …
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Building generative models over discrete structures : from graphical models to deep learning
… potential functions. Designed explicitly for efficient sampling, Perturbation Models are strong candidates for building generative models over structures, and the leading open questions pertain to understanding the properties of the induced models and developing practical learning algorithms.
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Sources of variability in nitrogen availability in Iowa cornfields
… is specifically needed to aid in design of efficient sampling strategies for the late-spring test for nitrogen (N) availability, which is a new management tool that enables site-specific evaluation and adjustment of fertilization practices. One study assessed the importance of windrows of …
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Physics-informed Machine Learning with Uncertainty Quantification
… Neural Networks (PINNs), and develop an efficient sampling strategy to mitigate the failure modes.
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Leveraging Gaussian Process Sampling for Sensitivity Analysis and Optimization in Engineering Design
… to this challenge. GPs inherently facilitate efficient sampling strategies, enabling informed decision-making under uncertainty by extracting information from a subset of potential functions for the model of interest. Despite their widespread use in machine learning and scientific computing, …
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Sampling Using Controlled Quantum Walks
… which uses random walks with stopping rules. Efficient sampling is an important computational task used in simulations based on stochastic processes. This is the first quantum algorithm that achieves a quadratic speed-up for sampling from general probability distributions over graph vertices. …
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Modeling the flexibility of alpha helices in protein interfaces : structure based design and prediction of helix-mediated protein-protein interactions
… methods requires models that can be used to efficiently sample structural variation. This thesis identifies methods that can be used to sample an important sub-space of protein structure: alpha helices that participate in protein interfaces. Helices, the global structural properties of which …
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A reformulated approach to attribute-aware sampling on large networks
Sampling has long been an important tool for extracting subsets of data for data mining tasks. As the scale of information produced has increased, efficient sampling is only becoming more important. Uniform sampling is often the preferred technique of choice, due to its simplicity and speed. …
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Statistical inference based on characteristic functions for intractable likelihood problems
… characteristic functions. In the first part, an efficient sampling method based on Bayesian empirical likelihood is developed. The method involves pseudo-marginal Markov chain Monte Carlo with temperature and is shown to be effective for Lévy processes. In the second part and third part, we study …
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Sequential Designs with Application in Software Engineering
… process. We started with a fully sequential sampling scheme to estimate the reliability of a software system using partition testing. We have shown both theoretically and through simulation that the proposed scheme always performs at least as well as fixed sampling approaches where test case …
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Max-Stable Processes, Measure Transport & Conditional Sampling
… event risk management in insurance. Conditional sampling and simulation methods, such as normalizing flows and measure transport, are crucial for estimating extremes at un-monitored sites or under specific conditions, thereby improving our understanding and risk management strategies. The goal of …
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Shaping light-matter interactions for free-electron radiation and photonic computing
… radiation and implementing Monte Carlo sampling algorithms in photonic circuits. We present a framework to model, tailor, and enhance radiation from free electrons and other high-energy particles interacting with nanophotonic structures. We then describe the building of a featured …
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