no code implementations • 24 May 2024 • Ali Rasekh, Reza Heidari, Amir Hosein Haji Mohammad rezaie, Parsa Sharifi Sedeh, Zahra Ahmadi, Prasenjit Mitra, Wolfgang Nejdl
Our motivation comes from the important areas of predicting mortality and phenotyping where using different modalities of data could significantly improve our ability to predict.
no code implementations • 6 Jun 2023 • Raneen Younis, Abdul Hakmeh, Zahra Ahmadi
Hence, in this work, we introduce a new framework for interpreting multivariate time series data by extracting and clustering the input representative patterns that highly activate CNN neurons.
1 code implementation • 28 Aug 2022 • Hoang H. Nguyen, Nhat-Minh Nguyen, Chunyao Xie, Zahra Ahmadi, Daniel Kudendo, Thanh-Nam Doan, Lingxiao Jiang
Moreover, it develops a multi-metapath heterogeneous graph attention network to learn multi-level embeddings of different types of nodes and their metapaths in the heterogeneous contract graphs, which can capture the code semantics of smart contracts more accurately and facilitate both fine-grained line-level and coarse-grained contract-level vulnerability detection.
no code implementations • 3 Feb 2021 • Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer
We use a topic model to extract topic- and sentence-specific evidence from the structured knowledge base Wikidata, building a graph based on the cosine similarity between the entity word vectors of Wikidata and the vector of the given sentence.
no code implementations • 15 Dec 2020 • Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer
Most deep neural networks are considered to be black boxes, meaning their output is hard to interpret.
no code implementations • 4 Apr 2018 • Zahra Ahmadi, Stefan Kramer
Many modern applications deal with multi-label data, such as functional categorizations of genes, image labeling and text categorization.