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 27 for “"A Bayesian inference"”.
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What and where : a Bayesian inference theory of visual attention
… in this thesis, attention is part of the inference process that solves the visual recognition problem of what is where. The theory proposes a computational role for attention and leads to a model that predicts some of its main properties at the level of psychophysics and physiology. In our …
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Efficient IC statistical modeling and extraction using a Bayesian inference framework
… called the MIT virtual source (MVS) model, and a Bayesian extraction method. Based on statistical formulations extended from the MVS model, we propose algorithms for three applications that greatly reduce time and cost required for measurement of on-chip test structures and characterization of …
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Bayesian inference algorithm on Raw
… hardware platform developed at MIT, running a Bayesian inference algorithm. Motivation for examining this parallel system is a growing interest in creating a self-learning and cognitive processor, which these hardware and software components can potentially produce. The Bayesian inference …
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Cooperate to compete : composable planning and inference in multi-agent reinforcement learning
… team plans and uses these plans as part of a Bayesian inference of collaborators and adversaries of varying intelligence. We study these models in two environments: a complex continuous Atari game Warlords and a grid-world stochastic game, and compare our model with human behavior.
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Generation and tuning of learned sensorimotor behavior by multiple neural circuit architectures
… how optimal sensorimotor estimation using a Bayesian inference framework could be implemented in a cerebellar circuit. Two novel behavioral paradigms are developed to assess how rats might tune their motor output to the statistics of the sensory inputs, and whether their behavior might be …
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Model parameter identification and model class selection in piezoelectric energy harvester based on bayesian inference
… (PEHs) using experimental data within a Bayesian inference setting is discussed. The implementation requires: a predictive model for the harvester response; an assumption for its prediction error; a prior multivariate probabilistic density function for the electromechanical properties; …
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Stochastic In-memory Computing Using Magnetic Tunnel Junctions
… fabricated in lab. The hardware designs for a Bayesian inference accelerator and Ising machine are also provided. Our results show magnetic tunnel junctions could open up rich design space for future computing hardware.
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Dynamic Bayesian Networks for Information Fusion With Applications to Human-Computer Interfaces
… a novel probabilistic approach based on dynamic Bayesian networks (DBNs). As a generalization of the successful hidden Markov models, DBNs are a natural basis for the general temporal action interpretation task. The problem of interpretation of single or multiple interacting modalities can then …
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Towards Models Mesoscale Chromatin Structure and Radiative DNA Damage via Computational Simulation
… We therefore sought to develop a structural inference tool for inferring mesoscale chromatin structures consistent with such contact data sets. We have built a Bayesian inference framework that combines a simplified worm-like chain model of DNA and steric interactions between nucleosomes with …
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Bayesian Variable Selection and Inference for Nonparametric Kernel Machine and Functional Models
… and functional data. In the first study, the Bayesian variable selection method is developed under a generalized fused multi-kernel machine regression. This method can apply to continuous/binary/ordered categorical response variables. We demonstrate the advantage of our method using …
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Modeling and numerical methods for power electronic devices
… circuit. An Elementary Effects algorithm and a Bayesian inference routine are used to fit the averaged model to a more expensive netlist model. State-space models can also be used with the sampled-data method for state vector simulation. This approach is more accurate than the averaged model, …
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The Zero Touch Experience : intent based contextual morphing on mobile devices using localized keyword distributions
… In this thesis, I present a technique to perform inference on user purpose and an implementation of that technique in a demonstration application called Concierge. Concierge showcases how purpose can be used to provide a compelling, personal mobile experience. The application uses a Bayesian …
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Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning
… improve RANS modeled Reynolds stresses. First, a Bayesian inference framework is proposed to quantify and reduce the model-form uncertainty of RANS modeled Reynolds stress by leveraging online sparse measurement data with empirical prior knowledge. Second, a machine-learning-assisted framework is …
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Bayesian modeling of microwave foregrounds
… models. The method of nested sampling [16, 5], a Bayesian inference technique for calculating the evidence (the average of the likelihood over the prior mass), promises to be efficient and accurate for modeling the microwave foregrounds masking the CMB signal. An efficient and accurate algorithm …
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Bayesian model selection with applications to radio astronomy
… of two main parts, both of which focus on Bayesian methods and the problem of model selection in particular. The first part investigates a new approach to computing the Bayes factor for model selection without needing to compute the Bayesian evidence, while the second part shows, through an …
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Defects and charge-carrier lifetime in early-stage photovoltaic materials : relating experiment to theory
… solar cells- and analyzed with the help of a Bayesian inference algorithm-to estimate the defect parameters that directly relate to lifetime. Collectively, these studies serve to provide a more robust framework for assessing and mitigating the presence of defects in early-stage PV materials, …
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Estimating spotted hyaena (Crocuta crocuta) population density using camera trap data in a spatially-explicit capture-recapture framework
… South Africa, was analysed using SPACECAP, a Bayesian inference-based SECR modelling program. Overall hyaena density for the reserve was estimated at 10.59 (sd=2.10) hyaenas/100 km2, which is comparable to estimates obtained using other methods for this reserve and some other protected areas …
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A Bayesian multilevel model for women unemployment in South Africa
… in South Africa. The classical and the Bayesian estimation approach were applied to a multilevel logistic regression (MLR) model. Secondary data acquired from the Demographic and Health survey (DHS) held in South Africa in 2016 was used in the study. Information criteria revealed that …
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Phylometagenomics: a new framework for uncovering microbial community diversity
… studies, I show that general Markov models in a Bayesian inference framework out- perform traditional, multivariate ecological methods in recovering true community structure. Applying this new methodology to Atlantic Ocean communities uncovered a distance-decay effect which was not revealed by …
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Optimization of Spectrum Allocation in Cognitive Radio and Dynamic Spectrum Access Networks
… national and regional agencies, we presented a Bayesian inference based prediction method, which utilizes prior information to make better prediction on channel availability. Finally a distributed channel allocation algorithm is designed based on the channel prediction results. We illustrated …
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