Tao Lin

Exploring the potential of multi-mask weight-tied models in machine learning.

JUNO aims to enhance detection of neutrinos from core-collapse supernovae.

JUNO employs new software tools to streamline neutrino research and data analysis.

Dynamic datasets enhance model learning and reduce resource needs.

Client2Vec enhances federated learning by creating unique identifiers for user data.

This study examines how bias affects belief changes in various fields.

A new framework enhances large model performance efficiently during fine-tuning.

JUNO aims to shed light on neutrinos' mysteries through advanced data processing techniques.

External memory banks enhance diffusion models for better image and sound creation.