Latest Articles for Machine Learning

A look into how neurosymbolic models combine programming and machine learning in graphics.

A new method enhances action recognition in video analysis.

Using self-supervised learning to forecast box office performance.

A new algorithm enhances data augmentation by using label information for improved model training.

A study comparing data augmentation techniques for enhancing computer vision models.

A new method enhances identification of known and unknown user intents in chatbots.

A new method improves accuracy in retrieving relevant text passages.

AOT-SNNs improve uncertainty estimation in spiking neural networks for better predictions.

A new method improves 3D models from noisy real-world scans.

This study evaluates ChatGPT's effectiveness in labeling social computing data.

FTMRate uses distance measurements to enhance Wi-Fi data rate choices.

Enhancing Gaussian processes through innovative self-distillation techniques.

A new method to enhance prediction accuracy and uncertainty estimates in machine learning.

This article discusses how to manage learning in agents with imposed constraints.

Combining episodic memory and reinforcement learning for faster and better decision-making.

Discover how machine learning transforms the study of celestial events and data analysis.

This study improves GNNs' ability to handle multi-node tasks using innovative labeling techniques.

New method enhances image recognition with limited examples.

Improving classification of SPNs through combined medical imaging and clinical data.

A new method improves clustering by aligning representations across multiple views.

A new chatbot combines images and text for improved user interactions.

Study reveals methods for extracting energy-related feedback from app reviews.

A look into how noise impacts consensus among agents and methods to optimize communication.

A new approach leverages graph structures for improved image tagging accuracy.

This study examines low-shot learning and its challenges in real-world computer vision.

This study tackles sentiment analysis in various African languages using advanced models.

A groundbreaking model enhances molecular representation for drug development.

Hybrid zonotopes simplify the study of neural networks using ReLU activation functions.

Research aims to forecast memorization behavior in language models for better privacy control.

A new method improves hyperspectral image quality by reducing noise effectively.

A new approach combining seeing, language understanding, and reasoning for better AI.

Introducing methods for safe exploration in reinforcement learning to minimize risks.

New training approach enhances predictions of zirconium's behavior with hydrogen.

GPT-4 shows promise in enhancing neural architecture search efficiency and effectiveness.

Exploring new methods for efficient imitation learning in machines.

GCNH improves learning from complex graph structures, tackling heterophily effectively.

SequeL simplifies Continual Learning experiments with PyTorch and JAX compatibility.

A look into how GNNs analyze graph data effectively.

Examining individual fairness in Bayesian models compared to traditional neural networks.

A new method enhances model efficiency in learning with limited data.