Latest Articles for Data Science

Discover how teleportation can improve optimization and generalization in machine learning.

A new model designed to analyze Romanian tweets using advanced technology.

A new method enhances the detection of manipulated videos through combined analysis.

A new method enhances semi-supervised community detection by focusing on node similarity.

A new method uses neural networks to measure magnetic fields in inaccessible vacuum chambers.

Researchers improve predictions of chaotic systems using diffusion models.

A new approach tackles challenges in knowledge graphs, focusing on accuracy and reliability.

New methods improve model flexibility and performance in audio tasks.

Learn how triclustering helps uncover patterns in complex tensor data.

A new hybrid method improves mutual information estimation by combining generative and discriminative techniques.

A novel approach using instance-wise data augmentation for better adversarial model robustness.

Training strategies impact language models' ability to retain knowledge over time.

New method improves finding solutions for complex problems using past data.

A look into masked pre-training and its connection to model performance.

New methods improve graph-based semi-supervised learning efficiency and speed.

A look at how consistency improves image generation in diffusion models.

Learn about efficient ways to prune neural networks for better performance.

Researchers find simpler models can compete with deeper networks in performance.

A look at the effectiveness of certified defenses versus adversarial training in machine learning.

Investigating prompt-based methods for improving language models in research data retrieval.

Comparing NF4 and AF4 for optimizing quantization in machine learning models.

This article discusses the significance of community detection in network analysis.

A new framework improves graph representation using self-supervised learning.

A new model seeks to clarify the inner workings of deep neural networks.

A new method enhances machine learning models to handle unknown classes during testing.

This study examines how advanced language models enhance speech recognition accuracy.

Examining the hurdles and potential of AutoML in the context of Large Language Models.

Insights on convergence rates and distribution behaviors in statistics.

A new framework for generating graphs using discrete representations and transformer models.

This article examines the effectiveness of feedback alignment in training neural networks.

Gode merges molecular graphs with knowledge graphs for better property predictions.

Research focuses on improving AI's reasoning abilities through human-inspired methods.

This study presents a new way to classify different types of ciphers using machine learning.

FlexCHarts adapts search spaces for deep neural networks to improve efficiency and performance.

Learn how Active Inference informs intelligent systems' decision-making and adaptability.

Assessing how language models handle contradictory information through BoardgameQA dataset.

This document explores sentiment analysis across different languages and cultures.

This article reviews methods for reducing EEG data complexity and topological analysis.

A new approach enhances model adaptability across diverse datasets.

New methods enhance the prediction of activity coefficients in liquid mixtures using machine learning.