这篇paper的核心idea主要就是dino-based的vit model + supervised contrastive learning 产生聚类性比较强的representations,然后使用 semi-kmeans 来进行聚类,具体可见代码,比较简单,这里就不啰嗦了。 https://github.com/sgvaze/generalized-category-discoverygithub.com/sgvaze/generalized-category-discovery 不过作为...
osr主要是为了解决封闭世界假设下,机器学习模型的预测过度自信的问题,即对于OOD样本,很多时候机器学习模型可能并不会因为样本是ood就给出[0.5,0.,5]这样低置信度的预测而是给出明确的例如[0.1,0.9]这样高置信度的预测,OSR 主要用于辅助分类模型不仅能够从已知的class中做正确的区分,同时还能够从未来数据中检测...
Generalized Category Discovery (GCD) aims to identify a mix of known and novel categories within unlabeled data sets, providing a more realistic setting for image recognition. Essentially, GCD needs to remember existing patterns thoroughly to recognize novel categories. Recent state-of-the-art method...
To address these challenges, we propose a novel computational framework, named AnnoGCD, building on Generalized Category Discovery (GCD) and Anomaly Detection (AD) for automatic cell type annotation. Our semi-supervised method combines labeled and unlabeled data to accurately classify known cell types...
Formally, we only have access to 𝒴𝒮subscript𝒴𝒮\mathcal{Y}_{\mathcal{S}} or seen categories during training time, while we aim to categorize samples from novel categories or 𝒴𝒰subscript𝒴𝒰\mathcal{Y}_{\mathcal{U}} during test time. For the Novel Class Discovery ...
We then introduce the Edge Explorer Model, which presents a novel class of adaptive walks, that perform faithful network discovery even on dense networks.doi:10.1209/0295-5075/92/50008Asztalos, A.Toroczkai, Z.arXivEplASZT ALOS A, TOROCZKAI Z. Network discovery by generalized random walks[J]...
A formidable challenge in uncertainty modeling in general, and when learning Bayesian networks in particular, is the discovery of unknown hidden variables. Few works that tackle this task are typically limited to discrete or Gaussian domains, or to tree structures. We propose a novel general purpose...
IASO Bio is a biopharmaceutical company engaged in the discovery and development of novel cell therapies and biologics for oncology and autoimmune diseases. IASO Bio possesses comprehensive capabilities spanning the entire drug development process, from early discovery to clinical development, regulatory appr...
对于one - class ND,一个示例学术基准可以与语义AD相同,它将MNIST as ID中的一个类和其余的类视为novel。多类ND对应的MNIST基准可能在训练时使用前6类,在剩余的4类上测试为OOD。评价ND的评估与AD相同,它基于AUROC、AUPR或 F-score (详见2.1节)。 备注:一类/多类二分法 虽然即使有多类注释,ND模型也不需要...
Fig. 2: The generalized model of TomoTwin locates novel proteins accurately. a, True-positive selected particles (white) and false negative (black) of the largest protein (PDB ID 2DF7) (896 kDa) in the generalization tomogram. b, The smallest protein (PDB ID 1FZG) (142 kDa) in ...