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Found 16 papers, 2 papers with code
Future-proofing geotechnics workflows: accelerating problem-solving with large language models
The integration of Large Language Models (LLMs) like ChatGPT into the workflows of geotechnical engineering has a high potential to transform how the discipline approaches problem-solving and decision-making.
Pathway to a fully data-driven geotechnics: lessons from materials informatics
This paper elucidates the challenges and opportunities inherent in integrating data-driven methodologies into geotechnics, drawing inspiration from the success of materials informatics.
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks
The design variables consist of a set of reactants in a reaction network and its network topology.
A General Class of Transfer Learning Regression without Implementation Cost
We propose a novel framework that unifies and extends existing methods of transfer learning (TL) for regression.
Morphology-rich Alphasyllabary Embeddings
Word embeddings have been successfully trained in many languages.
Recovering compressed images for automatic crack segmentation using generative models
We develop a recovery framework for automatic crack segmentation of compressed crack images based on this new CS method and demonstrate the remarkable performance of the method taking advantage of the strong capability of generative models to capture the necessary features required in the crack segmentation task even the backgrounds of the generated images are not well reconstructed.
A Bayesian algorithm for retrosynthesis
The identification of synthetic routes that end with a desired product has been an inherently time-consuming process that is largely dependent on expert knowledge regarding a limited fraction of the entire reaction space.
Data augmentation in microscopic images for material data mining
Recent progress in material data mining has been driven by high-capacity models trained on large datasets.
Personalized Radiotherapy Design for Glioblastoma Using Mathematical Models, Multimodal Scans and Bayesian Inference
Here we provide a Bayesian machine learning framework for the rational design of improved, personalized radiotherapy plans using mathematical modeling and patient multimodal medical scans.
Computational Engineering, Finance, and Science
Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events
Domain-specific annotations for NLP are often centered on real-world applications of text, and incorrect annotations may be particularly unacceptable.
On Developing Resources for Patient-level Information Retrieval
Privacy concerns have often served as an insurmountable barrier for the production of research and resources in clinical information retrieval (IR).
Robust Bayesian compressive sensing with data loss recovery for structural health monitoring signals
The application of compressive sensing (CS) to structural health monitoring is an emerging research topic.
