Latest Articles for Data Science

Exploring how repetition enhances continual learning in changing environments.

New methods improve graph communication and node distinction in GNNs.

A method to enhance fairness in classification models for sensitive areas.

A new system offers real-time monitoring and better forecasts for solar power generation.

A new measure improves divergence comparisons among multiple probability distributions.

A method to improve AI performance while ensuring clear decision-making.

Explore how machine translation improves multilingual classifiers with innovative techniques.

Exploring the intersection of quantum science and machine learning.

Combining LiDAR and camera data to improve self-driving technology efficiency.

Improving classifiers by managing uncertainty and enhancing reliability in critical applications.

This article discusses the importance and challenges of out-of-distribution detection in machine learning.

A new approach enhances the accuracy of reasoning graphs from language inputs.

Innovative methods refine ontology embeddings for better knowledge base completion.

Research explores machine learning's role in finding coronary artery blockages.

Learn effective methods to quantize LLMs while maintaining accuracy and performance.

This article discusses how trees can help analyze complex data interactions.

This article examines how fine-tuning affects language models' accuracy and hallucinations.

Exploring how disagreement in data labeling can provide valuable insights.

Researchers use synthetic solar images to improve flare prediction accuracy.

New methods improve audio representation through self-supervised learning techniques.

A new method enhances the efficiency of deep neural networks through automated optimization.

A look at new methods for calculating confidence intervals in mechanical shock testing.

This framework improves text evaluation efficiency and accuracy using Large Language Models.

Learn about methods to find optimal solutions in various fields.

A new method improves DBSCAN's efficiency for high-dimensional datasets and streaming data.

Introducing sharpness-aware minimization to improve feature construction in genetic programming.

A look at the importance of permutation tests in time series analysis.

Using LLMs to improve adaptation in MLOps.

COLOR framework enhances accuracy and efficiency in querying graph data.

This study investigates memory efficiency in large language models through low-rank decomposition.

VSGD combines traditional methods with probabilistic modeling for better deep learning optimization.

A new dataset ProCIS enhances conversational information seeking.

Exploring the benefits and challenges of shared variable embeddings in machine learning.

HuBMAP aims to create a detailed model of the healthy human body.

Introducing CLAMP, a new method to enhance continual learning across various domains.

Context Neural Networks improve forecasting accuracy by using related time series insights.

A new approach to enhance contrastive learning through adaptive data augmentation techniques.

This paper discusses methods to learn system dynamics using limited and noisy data effectively.

A new approach to improve document retrieval through optimized indexing.

New model allows precise control of voice qualities while retaining content.