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 294 for “"Contrastive"”.
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Recognition memory reveals just how contrastive contrastive accenting is
… in the continuation was manipulated between non-contrastive (H* in the ToBI system) and contrastive (L+H*). On subsequent recognition memory tests, the L+H* accent increased hits to correct statements and correct rejections of the contrast item (Experiments 1-3). L+H* did not impair memory for …
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Contrastive knowledge how
… practical knowledge requires acknowledging a contrastive dimension. A contrast set (or a set of alternatives) in epistemology refers to a group of propositions or possibilities that are relevant to a specific knowledge claim. When a person knows a fact, they don't just know that one specific …
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Contrastive Text Generation
… pipeline which can deal with a pair of contrastive inputs. Second, I describe an approach for multi-document summarization, where input articles have varying degrees of consensus. In a scenario with very few parallel data points, we utilize a planner to identify key content and consensus …
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Contrastive Learning of Auditory Representations
Learning rich visual representations using contrastive self-supervised learning has been extremely successful. However, it is still a major question whether we could use a similar approach to learn more efficient auditory and audio-visual representations. In this thesis, we expand on prior …
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Contrastive representation learning for bioimage quantification
… neural networks. In particular, self-supervised contrastive learning has shown remarkable success in domains such as vision and language. In this thesis, I extend and adapt contrastive learning techniques to address problems in bioimage analysis and beyond. I start by discussing representation …
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Contrasting contrastive and supervised models interpretability
… compare the representations of an unsupervised contrastive model to those of an equivalent supervised model using several deep neural network interpretability methods: network dissection, sparsity experiments, and saliency maps. Network dissections of self-supervised contrastive and supervised …
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Argumentation pragmatics, text analysis, and contrastive rhetoric
The contrastive rhetoric hypothesis (Kaplan, 1966) predicts that language users across cultures will vary in the means they use to construct coherent discourse. The problem for contrastive rhetoric research is to develop a method for reliably describing this variation. To this end, a number of …
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Adversarial graph contrastive learning with information regularization
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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Dynamics of Gradient Flow with Contrastive Learning
Contrastive learning (CL), in di erent forms, has been shown to learn discriminatory representations for downstream tasks without the need of human labeling. In the representation space learnt via CL, each class collapses to a distinct vertex of a simplex on a hypersphere during training. This …
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Improving Natural Language Understanding via Contrastive Learning Methods
… text encoders, I proposed a series of effective contrastive learning methods, which supervise the encoders by enlarging the difference between positive and negative data sample pairs. In this thesis, I first present a theoretical contrastive learning tool, which bridges the contrastive learning …
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Comprehension and Production of Contrastive Reference in Autism
… reference in narratives, with fewer exploring contrastive reference, particularly in comprehension. The current study aims to address these questions by investigating both the comprehension and production of contrastive reference and informativeness in autistic children, aiming to enhance our …
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Understanding Doubly Center-Embedded Sentences Through Contrastive Focus
… in English. Lexically identical sentences with contrastive emphasis on NP1, NP2, or VP1, and a baseline version for comparison, were read aloud for recording and judged for comprehensibility. Contrast on NP2 and VP1 yielded higher comprehensibility judgments compared to baseline than contrast on …
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Towards General-purpose Vision via Multiview Contrastive Learning
… thesis instead proposes and studies multiview contrastive learning, which is based on a simple mathematical principle -- discriminating between samples from the joint distribution and samples from the product of marginals. We firstly introduce the general framework of multiview contrastive …
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Uncertainty-Inclusive Contrastive Learning for Leveraging Synthetic Images
… In this work, we present Uncertaininclusive Contrastive Learning (UniCon), a novel contrastive loss function that incorporates uncertainty weights for synthetic images during training. Extending the framework of supervised contrastive learning, we add a learned hyperparameter that weights the …
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