Tag: contrastive learning

HGACL-DRP achieved reported mean AUC values of 95.48% and 98.99% on two public cancer cell-line datasets in a computational drug-response ...

Recommender systems quietly shape much of modern digital life, deciding which films appear in your queue, which products surface in ...

Researchers have unveiled an unsupervised deep learning framework that clusters retinal fundus images by disease using only image-level labels, achieving ...

A new machine-learning framework called MB-SupConCon extends supervised contrastive learning to continuous responses, enabling more accurate and biologically interpretable prediction ...

Researchers combined diffusion-generated synthetic retinal images, contrastive self-supervised pre-training, and a five-model ensemble to reach 95.1 percent accuracy in diabetic ...

Researchers at Liaoning Normal University have developed MCC-ED, a multi-module AI framework that combines contextual interaction, closed-loop graph fusion, and ...

Researchers in Würzburg developed CAFEx, a weakly supervised AI pipeline that uses an anatomical bottleneck to estimate cardiac ejection fraction ...

Researchers have combined contrastive learning with side-channel collision attacks, boosting key-recovery success rates by up to nearly 78 percent across ...

Researchers at Shanghai Jiao Tong University have built a multimodal knowledge graph that aligns historical Chinese architectural texts, field photographs ...

Researchers at the Beijing Institute of Technology show that adding expert-vetted relational graphic structure to AI models enables retrieval of ...