Figure - available via license: Creative Commons Zero 1.0
Content may be subject to copyright.
Test MRR comparison for snapshot and event-based methods on DTDG datasets, results reported from 5 runs. Top three models are coloured by First, Second, Third.
Source publication
Temporal graphs have gained increasing importance due to their ability to model dynamically evolving relationships. These graphs can be represented through either a stream of edge events or a sequence of graph snapshots. Until now, the development of machine learning methods for both types has occurred largely in isolation, resulting in limited exp...
Context in source publication
Context 1
... 0.121 ± 0.010 0.233 ± 0.008 0.192 ± 0.001 0.253 ± 0.006 0.126 ± 0.009 GCN (UTG) [9] 0.068 ± 0.009 0.164 ± 0.011 0.104 ± 0.002 0.289 ± 0.008 0.084 ± 0.010 [15] 0.398 ± 0.007 0.195 ± 0.001 0.321 ± 0.009 GCN (UTG) [9] 0.336 ± 0.009 0.186 ± 0.002 0.242 ± 0.005 CTDG Results. Table 3 shows the performance of all methods on the CTDG datasets. Similar to DTDG datasets, DyGformer and NAT retains competitive performance here. ...Similar publications
Purpose: To develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI, and compare models trained on datasets with aneurysm-like differential diagnoses. Methods: This retrospective study (2020-2023) included 385 anonymized 3D TOF-MRI images from 364 patients (mean...
In deep learning, CNNs are powerful tools for various applications. Manual architecture selection is time-consuming, limiting dataset exploration. This paper introduces a novel algorithm for CNN architecture, revolutionizing the way models are designed and evaluated. By providing the number of convolutions and essential hyperparameters, researchers...
The practice of pharmacovigilance relies on large databases of individual case safety reports to detect and evaluate potential new causal associations between medicines or vaccines and adverse events. Duplicate reports are separate and unlinked reports referring to the same case of an adverse event involving a specific patient at a certain time. Th...
The aim of this study was to develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI and compare models trained on datasets with aneurysm-like differential diagnoses. This retrospective study (2020–2023) included 385 anonymized 3D TOF-MRI images from 345 patient...
A bstract
Effective management of forest ecosystems requires accurate predictions of damage by ungulates, a challenge particularly acute in the Kyiv Polissya. This study aims to identify key drivers of ungulate browsing intensity and compare the effectiveness of the random forest model (RFM) and generalized linear model (GLM) in forecasting damage...
