Global ETD Search
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Showing 1 to 5 of 5 for “"Conditional score"”.
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Measurement Error Models in Shape Analysis
… (OPA), matching of two shapes based on the conditional score method. In the measurement error literature the conditional score method is widely applicable for models of real variables and it yields consistent inference. We develop the conditional score method for two and three dimensional …
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Topics in Deep Generative Modelling Mathematical and Computational Aspects of Diffusion Models and Generative Adversarial Networks
… generative models with a special emphasis on score-based diffusion models. It also includes studies of theoretical underpinnings of generative adversarial networks and introduces novel algorithmic improvements to variational autoencoders. The work contributes both theoretical insights and …
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Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry
… manifolds. In chapter 3, we introduce CAFLOW, a conditional normalising flow that improves image-to-image translation by hierarchically modelling image distributions across scales. In chapter 4, we introduce non-uniform diffusion models, which apply faster diffusion speed to high-frequency …
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Time Series Models for Finance and the Environment
… is based on the novel observation-driven dynamic conditional score (DCS) class of time series models. The first chapter sets up a DCS model based on the Generalised Beta of the second kind conditional distribution for modelling realized volatility (RV). Given its general formulation, it is capable …
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Mixed Effects Modeling and Correlation Structure Selection for High Dimensional Correlated Data
… to estimate fixed and random effects using conditional quadratic inference functions. The new approach does not require any specification of the likelihood functions. It can also accommodate serial correlation between observations within the same cluster, in addition to mixed-effects …