Tag: representation learning

A new study shows that how wearable sensor data is translated into language-model inputs—raw numbers, category labels, or both—critically shapes ...

The study, published in Frontiers in Neurorobotics by researchers at Chiba Institute of Technology, arrives at a moment when the ...

Researchers at Central South University have developed a cluster-based domain adaptation method that aligns only semantically similar portions of source ...

Researchers at Hanyang University have developed TACCO, a contrastive learning method that explicitly identifies and suppresses out-of-distribution actions to stabilize ...

Researchers have developed ALTAI, a neural network that aligns character, word, and semantic representations through cross-granularity contrastive learning to achieve ...

A new survey argues that the evolution of deep clustering is fundamentally the evolution of the prior knowledge embedded in ...

A new shapelet-based soft contrastive learning framework called SCLS improves multivariate time series clustering by avoiding noisy data augmentation and ...

Researchers in China have developed a Multimodal Transformer Attention model that jointly extracts and fuses video, audio and text features ...

Researchers have developed an end-to-end graph neural network framework that jointly learns expert representations to find both individual experts and ...

A UCLA mathematician has introduced a distance-based representation learning framework grounded in coarse geometry that reads the global shape of ...