We apply topological data analysis (TDA) to 108 genetic regulatory circuits from GLMP. Each circuit is represented as a Mermaid Markdown flowchart derived from textual process descriptions. The most ...

Abstract: For many years, topological data analysis (TDA) and deep learning (DL) have been considered separate data analysis and representation learning approaches, which have nothing in common. The ...

It is a central question in neuroscience to understand how different regions of the brain interact, how strongly they "talk" to each other. Researchers from the Max Planck Institute for Mathematics in ...

In the golden hills of Puglia, a southern region of Italy known today for its olive trees, white cliffs and turquoise mediterranean coves, Lorenzo Avello has artificial intelligence on his mind.

This repository contains the implementation of topological data analysis (TDA) methods for detecting adversarial examples in deep learning models, particularly focusing on Vision-Language models like ...

Researchers develop a novel topology-aware multiscale feature fusion network to enhance the accuracy and robustness of EEG-based motor imagery decoding Electroencephalography (EEG) is a fascinating ...

Artificial intelligence has developed rapidly in recent years, with tech companies investing billions of dollars in data centers to help train and run AI models. The expansion of data centers has ...

For a more detailed explanation for this package, this document will keep update for better understanding the source code. You can also try the playground I build to get familier with the algorithm ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...