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Rewriting a Deep Generative Model
Published 2021“…© 2020, Springer Nature Switzerland AG. A deep generative model such as a GAN learns to model a rich set of semantic and physical rules about the target distribution, but up to now, it has been obscure how such rules are encoded in the network, or how a rule could be changed. …”
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Software Library for Generative Model Applications
Published 2023“…In this thesis, we focus on building a software library to facilitate the workflow, evaluation, and analysis of generative models. Our work is primarily aimed at helping a specialty chemicals company use a state of the art molecule generation model for their specific applications. …”
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Listening with generative models
Published 2023“…This thesis extends classic traditions in perception by leveraging contemporary tools to build and apply rich generative models that describe what we hear. First, I present a hierarchical Bayesian auditory scene synthesis model to address the perceptual organization of sound into sources and events. …”
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Generative Modeling with Guarantees
Published 2023“…Therefore, this thesis aims to develop techniques that balance guarantees and utility, focusing on improving the reliability of generative models while preserving their flexibility. …”
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Generative model for reciprocity and community detection in networks
Published 2021-06-01“…We present a probabilistic generative model and efficient algorithm to model reciprocity in directed networks. …”
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A Generative Model for Correlated Graph Signals
Published 2021-11-01Subjects: Get full text
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On Physics-Inspired Generative Models
Published 2024“…Physics-inspired generative models such as diffusion models constitute a powerful family of generative models. …”
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Co-Clustering with Generative Models
Published 2009“…In this paper, we present a generative model for co-clustering and develop algorithms based on the mean field approximation for the corresponding modeling problem. …”
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Generative models: theory and applications
Published 2023“…<p>Given some samples from a data distribution, the central aim of generative modeling is to generate more samples from approximately the same distribution. …”
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Generative models as distributions of functions
Published 2022“…Generative models are typically trained on grid-like data such as images. …”
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A generative model of electrophysiological brain responses to stimulation
Published 2024-01-01Subjects: Get full text
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Human Activity Recognition with an HMM-Based Generative Model
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A Bayesian Generative Model for Learning Semantic Hierarchies
Published 2014-05-01“…In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. …”
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