Tech Xplore

This AI mines the numbers buried in scientific papers and turns them into usable data fast

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.
IEEE

Representation Learning for Tabular Data: A Comprehensive Survey

Abstract: Tabular data, structured as rows and columns, is among the most prevalent data types in machine learning classification and regression applications. Models for learning from tabular data ...
VentureBeat

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...
Forbes

From Text To Tables: Why Structured Data Is AI’s Next $600 Billion Frontier

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. In the current wave of generative AI innovation, industries that live in documents and text ...
IEEE

MRLF: Multimodal Representation Learning for Tabular Data Classification

Representation learning fundamentally determines the classification performance of models on tabular data. However, existing tabular data classification models typically focus on single-modal encoding ...
Scientific Research Publishing

Research on the Nonlinear Impact of Investor Sentiment on Stock Returns Based on Deep Learning and Text Mining ()

This paper focuses on the nonlinear correlation between investor sentiment and stock returns and conducts in-depth research with the aid of deep learning and text mining techniques. First of all, sort ...
Frontiers

YOLOv8-Seg: a deep learning approach for accurate classification of osteoporotic vertebral fractures

This study investigates the application of a deep learning model, YOLOv8-Seg, for the automated classification of osteoporotic vertebral fractures (OVFs) from computed tomography (CT) images. A ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...