Abstract: Spatio-temporal data like a Dynamically Weighted Directed Network (DWDN) are ubiquitous in bigdata applications like an intelligent recommender system. They commonly illustrate the complex ...

Tensor has unveiled its personal Robocar at CES, positioning it as an AI-first autonomous vehicle built from the ground up for Level 4 driving rather than a conventional EV retrofitted with autonomy.

Tabular artificial intelligence startup Prior Labs GmbH today announced a new foundation model that can handle millions of rows of data to give enterprises a way to understand and use their most ...

Abstract: A novel reinforced dual-flow neural network based on attention and a polynomial-based radial basis function network (DFBTP) is proposed to enhance classification performance on tabular data.

When the FORTRAN programming language debuted in 1957, it transformed how scientists and engineers programmed computers. Complex calculations could suddenly be expressed in concise, math-like notation ...

Leading power, open roots: Olmo 3 introduces full model flow transparency and traceability, combining top-tier performance with increased efficiency and cost savings to advance open and sustainable AI ...

Researchers have demonstrated a new optical computing method that performs complex tensor operations in a single pass of light. The advance could reshape how modern AI systems process data and ease ...

Explore the Kaggle Grandmasters' strategies for mastering tabular data, including GPU acceleration techniques, diverse baselines, and feature engineering. Discover how these methods can enhance ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...