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Showing 1 to 5 of 5 for “"Multimodal representation learning"”.
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Multimodal Representation Learning for Medical Image Analysis
My thesis develops machine learning methods that exploit multimodal clinical data to improve medical image analysis. Medical images capture rich information of a patient’s physiological and disease status, central in clinical practice and research. Computational models, such as artificial neural …
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Multimodal Representation Learning for Agentic AI Systems
… the efficiency and robustness of cross-modal representation learning methods. Our approach utilizes progressive self-distillation and soft image-text alignments to model the many-to-many correspondences found in noisy web-harvested datasets. Extensive evaluation demonstrates that our method …
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Multimodal Representation Learning for Textual Reasoning over Knowledge Graphs
… search. This creates a need for multi-modal representations that capture both the semantic and structural features from the KGs. The primary objective of the proposed work is to extend the accessibility of KGs to non-expert users/institutions by enabling them to utilize non-technical textual …
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Multimodal Robot Systems and Learning
… the engineering design and system analysis of a multimodal, robotic environment. We first give background on why this type of system is unique, describing the different approach we take to sensing, dynamics, and control. We then delve into the robot itself, and review our development of a python …
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Multimodal learning and language models for enhanced knowledge representations
Machine learning with modern neural architectures, particularly large-scale language models, has enabled impressive progress across diverse problem domains such as natural language processing, graph representation learning, and tabular data analysis. However, these successes have predominantly …