Bauer, J., Sattler, U., Parsia, B.: Explaining by example: model exploration for ontology comprehension. In: Description Logics. CEUR Workshop Proceedings, vol. 477. CEUR-WS.org (2009) Google Scholar Bishop, C.M.: Pattern Recognition and Machine Learning. Information Science and Statistics...
全面调研了针对大型视觉语言模型的各类攻击方法,包括技术实现、利用的模型漏洞、当前局限以及未来方向。 [LG] Explaining Graph Neural Networks for Node Similarity on Graphs https://arxiv.org/abs/2407.07639 图神经网络(GNN)可以高效地计算图上的节点相似度,但是当GNN用于需要可解释性的应用时,其预测结果也需要解...
Dink-Net: Neural Clustering on Large Graphs 刘悦、夏俊 李子青实验室访问学生、李子青实验室2020级博士生 背景知识 深度图聚类(Deep Graph Clustering)方法旨在利用深度神经网络(Deep Neural Networks, DNN),尤其是图神经网络(Graph Neural Networks, GNNs),将图中的节点划分为不同的簇,使得簇内样本相似度最大...
After being confined for 2 months and hearing the word pandemic almost daily, seeing graphs, opinions, time lines and values that rise and fall, I…Read More » Covid19 : Chapter 1 : Need of a Master Algorithm PreetSharma643 May 17, 2020 at 5:30 am ...
There are no missing values, and all remaining attributes are of type numerical, eliminating the need for dummy variable creation. For the descriptive analysis of the NBA gameplay, clustering analysis, trend analysis using line graphs, and PCA are employed. The data standardisation process (i.e....
Post-hoc approaches are effective for interpreting model complexity when there is a nonlinear connection or increased data complexity. In this scenario, the post-hoc technique is a handy tool for explaining what the model has learnt when the data and features do not follow a clear connection. ...
XAI - An eXplainability toolbox for machine learning Python The Institute for Ethical Machine Learning xplique Python XAIoGraphs Python Telefonica XAITK Python DARPA Zennit Python Interpretable Models imodels Python imodelsX Python interpretML Python Microsoft R PiML Toolbox Python Tensorflow Lattice Pyt...
Visualization Wizard:The R program is ideal for creating stunning and insightful charts and graphs that showcase its results. It can transform complex data into simple-to-understand data. R does indeed have a slightly steeper learning curve than Python. R’s syntax can be different, and using ...
In this paper, we argue for a paradigm shift from the current model of explainable artificial intelligence (XAI), which may be counter-productive to better human decision making. In early decision support systems, we assumed that we could give people recommendations and that they would consider ...
Semantic Networks: It represents knowledge graphs, semantic net or ontologies. It is again more into the direction of System 2. One shot learning here is easier by disconnecting or connecting two facts (nodes). Frames: A frame is a data structure with typical knowledge about a particular object...