Zhen Zhang

Study uncovers properties of ternary borides for electronics and energy storage.

A2GNN model enhances performance in adapting graph knowledge across different domains.

LinkNER combines NER models and LLMs for better named entity recognition.

BuffGraph improves classification for less common classes in imbalanced graph data.

A novel approach to graph domain adaptation without needing labeled data.

This study reveals insights into ultrafast electronic processes using advanced techniques.

New methods aim to improve model performance on unseen data.

This article discusses robust accurate fairness in deep learning and its effects.

Examining new developments in tools for verifying complex systems.

Discover strategies for efficient resource allocation in deep learning.

Examining how medium-range order affects the behavior of silicate glasses.

A look into the challenges and innovations in graph domain adaptation methods.

A new subclass of gamma-ray bursts offers fresh perspectives on cosmic explosions.

A look into how dynamic graphs shape our interactions and insights.

A fresh approach to improving learning amid noise in reinforcement learning environments.

InvariantStock offers stable stock predictions in changing market conditions.

New method enhances analysis of complex systems through Symplectic Graph Neural Networks.

A groundbreaking gamma-ray burst reveals insights into cosmic phenomena.

Combining neural and diffusion models improves accuracy in turbulence predictions.

An overview of how our blood system and stem cells function.

Mamba simplifies beamline tuning processes, enhancing scientific experiments.

Understanding how DPS complicates measurements of the Z boson mass.

New methods enhance how language models respond, balancing knowledge and current events.