「self-supervised」の検索結果
17 件Self-supervised learning relies on so-called data augmentations $φ(x)$ of unlabeled datapoints $x$ --- for exa
Biological agents navigate familiar environments not by re-solving routes for each new goal, but by reusing a
The abundance of online data is at risk of unauthorized usage in training deep learning models. To counter thi
Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a g
Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-v
Hyperspectral and multispectral image fusion (HMIF) aims to reconstruct a high-resolution hyperspectral image
We explore the use of simulated data for training a model for protein annotation in crowded cryo-electron tomo
Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific deco
Vision foundation models (VFMs) are valuable in data-scarce domains such as surgery, where a single pretrained
Object-centric visual representations are important for physical-world perception, but existing visual pretrai
We introduce S$^3$T (Self-Supervised Self-Distillation over Time), which, to the best of our knowledge, is the
While deep generative models offer new opportunities for medical image synthesis and data sharing, their abili
Advances in neural rendering have enabled high-fidelity multi-view reconstruction of 3D scenes. However, free-
Self-supervised pretraining has transformed language and vision, but its value for molecular graph neural netw
Vision Transformers (ViTs) typically process every image using a fixed input resolution and model width, even
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
動的グラフの構造と意味のパターンを捉えるため、最新の研究では、ラベル付けされたデータの欠如に対応するために、生成的または対比的のパラダイムを導入する。ただし、これらの方法は複雑なエッジレベルからの再構築の目標に依存し、グ