Latest Articles for Data Science

A fresh method to understand causal relationships in dynamic environments.

Exploring the use of RTDETR for safer roads in Bangladesh.

A look at bias in AI and how to tackle it fairly.

Using galaxies' relationships, a GNN predicts dark matter halo masses more accurately than traditional methods.

Using synthetic data to improve facial emotion recognition accuracy in machines.

A new method generates realistic data for training models in identity verification.

A simple overview of PL and LS constants in optimization and data analysis.

Using LLMs to classify and promote green practices on social media.

This research improves Knowledge Graphs using refined negative sampling techniques for better model performance.

Learn the basics of quantum programming and its unique concepts.

Scientists use data and simulations to speed up material discovery.

A new dataset enhancing video understanding and AI reasoning.

KBAlign helps machines learn faster and more effectively through self-questioning techniques.

A look into sampling methods and their applications in data science.

A new method aims to make genetic risk scores more accurate for diverse ancestries.

Researchers develop methods to ensure fairness in machine learning systems.

LISA will listen to gravitational waves, unveiling cosmic secrets.

Using language to improve data classification across varying settings.

A look into causal inference methods and the role of Structural Causal Models.

AeroGen generates synthetic images to improve object detection in remote sensing.

CAMA enhances federated learning efficiency while reducing energy consumption and emissions.

Mamba-CL improves AI learning by retaining old knowledge while acquiring new tasks.

Learn about network planning and interference solutions in mobile networks.

Learn how stability selection sharpens focus on important data variables.

A new method improves the detection of anomalies in machine learning.

Learn how to train computers to recognize images without bias.

SuperGCN improves training efficiency for large graphs using advanced CPU techniques.

A look into how weight matrices influence machine learning models.

A look at how AutoML improves network intrusion detection.

Discover how DANNs reshape data analysis with flexibility and efficiency.

Discover innovative methods for sampling signals using graph theory.

Using Freq-Synth to improve predictions with limited data.

Learn how to optimize video generation models effectively to achieve impressive results.

Discover how oblique trees improve data predictions by considering multiple features.

GSEBO reveals how to better understand complex graph connections.

Learn how Gaussian Mixture Models enhance GNN performance through data augmentation.

A new method leverages gravity concepts to effectively prune deep convolutional neural networks.

A look into Jupyter notebooks' crashes and how to prevent them.

Exploring cosmic curvature helps reveal the universe's shape and expansion.

Synthetic images enhance training data for self-driving cars in challenging conditions.