Flexible body dynamics simulations are powerful tools to realistically analyze vehicles, machines, mechanics, etc. However, the inherently nonlinear governing equations often require tailor-made and computationally expense solution strategies. Employing artificial neural networks for forward dynamics analyses of...
Institute of Cardiovascular Regeneration, University Hospital and Goethe University Frankfurt, Frankfurt, Germany Marcel H. Schulz Contributions M.L. conceived this Review, supervised and contributed to the writing of the manuscript. M.S., F.S. and O.L. collected information about the tools and da...
Tissue clearing methods enable the imaging of biological specimens without sectioning. However, reliable and scalable analysis of large imaging datasets in three dimensions remains a challenge. Here we developed a deep learning-based framework to quantif
Machine learningCancerLinguistic analysisExpression of emotion has been linked to numerous critical and beneficial aspects of human functioning. Accurately capturing emotional expression in text grows in relevance as people continue to spenddoi:10.1007/s41347-017-0015-5O’Carroll Bantum, Erin...
cholesterol; hypercholesterolemia; long-term prediction; machine learning; data analysis1. Introduction Cholesterol is a form of fat and a key component of cells. It plays a very important role in health as it participates in the synthesis of hormones, in the production of vitamin D and in the...
Additionally, SHAP offers a suite of powerful visualization tools to aid in comprehending and interpreting complex machine learning models. This study uses SHAP to analyze the significance of each oxide in the input variables for the basalt elastic modulus, identify how input variables affect the ...
natural language processing, causal inference, as well as applications to health, with a current focus on public health and epidemiology. He also creates technology: he co-funded scikit-learn, one of the reference machine-learning toolboxes, and helped build various central tools for data analysis...
Learn about meta learning models with hybrid neural networks Create a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data logging Building conversational user interfaces (CUI) for chatbots Writing genetic algorithms that...
Machine learning (ML) provides methods, techniques, and tools to help solve diagnostic and prognostic problems in various medical domains. In recent years, ML algorithms have been more widely and increasingly applied in biomedical fields, for example, in autism spectrum disorder or asthma research, ...
Open3D-ML is an extension of Open3D for 3D machine learning tasks. It builds on top of the Open3D core library and extends it with machine learning tools for 3D data processing. This repo focuses on applications such as semantic point cloud segmentation and provides pretrained models that can...