Abstract: Existing unsupervised graph anomaly detection (GAD ... between a node and their neighboring subgraphs at multiple scales. From feature level, we employ a multi-layer representation ...
We then performed another double cue CS-US fear memory experiment to study the temporal characteristics of fear memory malleability to behavioral extinction at the short- (30mins), medium- (6 hours) ...
Kelowna-Lake Country-Coldstream MLA Tara Armstrong's decision to quit the BC Conservatives has intensified concerns about representation in her riding. Friday's news that Armstrong was leaving the ...
This section focuses on the key features and methods for working with linear graphs. It demonstrates how to sketch graphs from rules, derive rules from graphs, and calculate key features such as the ...
Giant trolley scales being trialled by Tesco have caused a mixed reaction with concerns that 'honest shoppers' are being 'treated like thieves'. Trolleys are weighed before checkout of those ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Despite the profound impact of Computational Chemistry (CC) on chemical research and ...
Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning
Modelling the periodicity and symmetry of inorganic crystalline materials poses unique challenges, which existing graph ML methods are unable to immediately address. Moving to inorganic nanomaterials ...
Abstract: Large-scale image and text representation learning is critical in determining the performance of multimodal tasks involving images and text, such as visual question answering and image ...
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