Representational Similarity Analysis (RSA)has become a popular and effective method to measure the representation of multivariable neural activity in different modes. NeuroRAis an easy-to-use toolbox based onPython, which can do some works aboutRSAamong nearly all kinds of neural data, includingbehav...
code for CVPR paper "Representation Similarity Analysis for Efficient Task Taxonomy and Transfer Learning" - kshitijd20/RSA-CVPR19-release
The representational similarity analysis (RSA)31 was utilized to evaluate the cross-subject similarity between these two affective spaces. Specifically, we calculated the correlations between the representational dissimilarity matrix (RDM) of the individual affective space and the sub-group affective space...
Similarity learningEnhancementAccurate identification of cell types from single-cell RNA sequencing (scRNA-seq) data plays a critical role in a variety of scRNA-seq analysis studies. This task corresponds to solving an unsupervised clustering problem, in which the similarity measurement between cells ...
它可以把一个单词表达成一个由实数组成的向量,这些向量捕捉到了单词之间一些语义特性,比如相似性(similarity)、类比性(analogy)等。我们通过对向量的运算,比如欧几里得距离或者cosine相似度,可以计算出两个单词之间的语义相似性。 模型目标:进行词的向量化表示,使得向量之间尽可能多地蕴含语义和语法的信息。
encoder-only LLMs can generate more effective representations for downstream tasks like material property prediction or similarity analysis. As has been verified by Trewartha et al.16, language models with extended materials science knowledge tend to perform better on materials science-related tasks, wit...
The KL divergence was computed using the scipy.spatial.cKDTree module in the SciPy library in Python. Briefly, the Euclidean distance was calculated between a given sample of the subtask manifold data in the PC space and its nearest neighbor within the same data (randomly sampled n points). ...
NMF analysis was carried out with Python sklearn library, minimizing the Frobenius norm. A hyperparameter search was carried out over the number of components to extract in PCAWG data, revealing a knee point at approximately 14 components, with 50 components showing reconstruction error convergence....
In graph-level representation learning tasks, graph neural networks have received much attention for their powerful feature learning capabilities. However,
The most significant area identified in the functional localizer task identified a region of the MPFC that was used for the self-esteem correlation analysis (Fig. 2A). Within this region, we found a significant association between each individual's self-esteem and the similarity of patterns of ...