Domain-adversarial graph neural networks for Λ hyperon identification with CLAS12
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/18/06/p06002
Abstract: Machine learning methods and in particular Graph Neural Networks (GNNs) have revolutionized many tasks within the high energy physics community. Particularly in the realm of jet tagging, GNNs and domain adaptation have been especially successful.… read more here.
Keywords: neural networks; hyperon identification; domain adversarial; graph neural ... See more keywords
Adversarial Graph Regularized Deep Nonnegative Matrix Factorization for Data Representation
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DOI: 10.1109/access.2022.3198976
Abstract: This work proposes a novel unsupervised deep non-negative matrix factorization (NMF) model called AGDNMF by deep exploration of the structure of the original data. Compared with the existing NMF research results, the model explores the… read more here.
Keywords: model; matrix factorization; adversarial graph;
Neighbor-Anchoring Adversarial Graph Neural Networks
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3087970
Abstract: Graph neural networks (GNNs) have witnessed widespread adoption due to their ability to learn superior representations for graph data. While GNNs exhibit strong discriminative power, they often fall short of learning the underlying node distribution… read more here.
Keywords: neighbor anchoring; neural networks; anchoring adversarial; graph neural ... See more keywords