Global ETD Search
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Showing 1 to 5 of 5 for “"Knowledge-Guided Machine Learning"”.
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Knowledge-Guided Machine Learning for Single-Cell Regulatory Genomics
… networks. This defense presents a set of knowledge-guided machine-learning approaches that embed prior biological evidence into modern analytical models to improve regulatory inference from noisy single-cell data. First, we evaluate TF-IDF transformations and dimensionality-reduction …
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Knowledge-guided Machine Learning for Sensor-based High-Performance Autonomous Material Characterization
Knowledge-guided machine learning enables sensor-based high-performance material characterization that drives accelerated materials discovery and manufacturing. Traditional materials discovery workflows are driven by low-throughput characterization processes that involve several manual sample …
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KGML-N: a knowledge guided machine learning modeling framework for efficient simulation of N-yield response
… a surrogate model KGML-N—a highly efficient machine learning model trained to emulate the functions of a comprehensive PB model (ecosys). We designed a Knowledge-Guided Machine Learning (KGML) model, named KGML-N, whose architecture is inspired by the known scientific principles of crop …
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Understanding The Effects of Incorporating Scientific Knowledge on Neural Network Outputs and Loss Landscapes
While machine learning (ML) methods have achieved considerable success on several mainstream problems in vision and language modeling, they are still challenged by their lack of interpretable decision-making that is consistent with scientific knowledge, limiting their applicability for scientific …
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Learning without Expert Labels for Multimodal Data
While advancements in deep learning have been largely possible due to the availability of large-scale labeled datasets, obtaining labeled datasets at the required granularity is challenging in many real-world applications, especially in scientific domains, due to the costly and labor-intensive …