Tag: self-supervised learning

A new unsupervised deep learning framework called SaDGAE uses a self-adaptive cell graph and a doubly enhanced graph autoencoder to ...

Researchers have developed DiffProNet, a framework that applies diffusion-inspired feature-space denoising to prototypical networks, achieving competitive few-shot fine-grained image classification ...

A new survey from the Shanghai AI Laboratory maps the explosive progress in 3D self-supervised pre-training, from contrastive learning and ...

Researchers at Soongsil University have developed a self-supervised, multi-view defense that detects label-flipping poisoning attacks in tabular machine learning by ...

Researchers at the Vellore Institute of Technology have built NEXUS-Rec, a five-signal neural recommender that outperforms strong baselines on MovieLens ...

A new statistical learning study shows that the apparent benefits of sophisticated multimodal emotion recognition architectures depend critically on independent ...

Researchers have developed a spectrum-guided, teacher–student AI framework that adapts its time windows to the rhythms of unlabeled system logs ...

Researchers have developed BHyGNN+, a self-supervised framework that learns representations of heterophilic hypergraphs without labels by contrasting each hypergraph against ...

Researchers have unveiled xvr, a self-supervised AI framework that adapts a pretrained neural network to any patient's anatomy in about ...

A large-scale study finds that pretraining tabular self-supervised models on carefully selected subsets of 100 to 1000 unlabeled examples often ...