使用DSNE可视化数据速度
Visualizing Data Velocity using DSNE
摘要：
我们提出了一种新的技术称为“DSNE”，学习的速度嵌入的低维地图点时，给定的高维数据点，其速度。该技术是随机邻域嵌入的一种变体，它利用点的单位长度速度与点到其近邻的单位长度方向之间在单位球面上的欧氏距离来定义相似性，并尝试在高维空间和低维空间中匹配这两种相似性，以找到低维空间上的速度嵌入。DSNE可以通过在二维或三维空间中呈现数据点的运动，帮助可视化数据点在高维空间中的运动。这有助于了解细胞分化和胚胎发育的机制。
英文摘要：
We present a new technique called "DSNE" which learns the velocity embeddings of low dimensional map points when given the high-dimensional data points with its velocities. The technique is a variation of Stochastic Neighbor Embedding, which uses the Euclidean distance on the unit sphere between the unit-length velocity of the point and the unit-length direction from the point to its near neighbors to define similarities, and try to match the two kinds of similarities in the high dimension space and low dimension space to find the velocity embeddings on the low dimension space. DSNE can help to visualize how the data points move in the high dimension space by presenting the movements in two or three dimensions space. It is helpful for understanding the mechanism of cell differentiation and embryo development.
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